Bilingualism

Heritage Language, Linguistic Proximity Model, Language Learning Heritage Speakers and L3 Learning: Impacts on New Language Development

Victoria Sauceda, Remi Akopians, Elizabeth Escamilla, Stella Kang, Karoline Vera

Why do some languages feel easier to learn than others? For heritage speakers or individuals who grow up speaking a minority language at home while navigating the dominant language of their community, acquiring a third language (L3) comes with its own set of challenges and benefits. This study investigates whether linguistic proximity between languages makes L3 acquisition easier, focusing on Spanish heritage speakers who are learning either Parisian French, a close Romance language, or Seoul Korean, a linguistically distant language in the Koreanic language family.

Our research study examines phonetics, particularly vowel perception, to explore how proximity among language families influences language learning. In the listening comprehension methodology this study employs, participants who identified as Spanish heritage speakers and beginner or intermediate learners of French or Korean were instructed to identify shared vowels such as /a/, /i/, /o/, /u/ in all three languages or Spanish, French, and Korean. If one group had a higher accuracy percentage in identifying more of these vowels than the other, this finding could indicate that certain factors, such as linguistic proximity play an important role in learning a third language. Overall, this blog builds on these findings to explore their implications for understanding heritage speakers’ third-language acquisition experience.

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Introduction and Background

Heritage learners navigate the cross-section between their home language and the dominant language in their broader societal environment, providing a unique perspective on multilingualism. A heritage learner is typically an individual raised in a household where a language other than the societal majority language is spoken, leading to high proficiency levels in both languages. Unlike general multilingual individuals, heritage learners often experience imbalanced exposure to their languages due to the switch to another dominant language, influencing their learning trajectory.

The research investigates the differences between acquiring a third language within the same language family and learning a language from a distinct family, focusing on Spanish heritage speakers. It examines the experiences of Mexican Spanish speakers who have acquired English as their second language and they are now learning Parisian French compared to Seoul Korean which is part of the koreanic family. The research aims to understand how heritage speakers handle multilingualism and the linguistic and cognitive elements influencing language acquisition outcomes.

We know that a heritage speaker can be someone who grows up speaking a minority language at home while being exposed to the dominant language in their community. Research on heritage language speakers suggests early exposure to a minority language has a major impact on their linguistic and cognitive abilities when compared to monolinguals and second-language learners. According to Westergaard’s (2016) findings, which support the Linguistic Proximity Model (LPM), both previously acquired languages impact subsequent L3 acquisition, implying that structural similarity is an important aspect in third language learning. In a more recent study, Deng (2022) analyzed the comprehensibility of tone 3 sandhi production between Mandarin and Cantonese heritage learners and non-heritage learners and found no significant differences.

These studies and researchers provide an understanding of how past linguistic knowledge influences language acquisition. The final study I will discuss supports and complements the two previous ones presented even though it is more focused on grammar, sentence structure, and production. Hopp’s (2014) study compares Turkish-German bilingual children with German monolingual children studying English as a third language to investigate the study of cross- linguistic influence on grammar. Why Hopp(2014) found regarding cross linguistics how the bilingual group’s English grammar learning was impacted by their first and second languages with the impact differing depending on the common linguistic elements. With this, we see Hopp(2014) supports Westgaard(2016) by emphasizing that cross-linguistic impact is influenced by structural similarities and language dominance which align with the LPM model.

Deng (2022) focuses on how heritage learners’ linguistic memories impact their ability to learn phonological rules, providing an in-depth assessment of specific learning challenges. Westgard (2016)gives a larger approach highlighting the importance of linguistic proximity and selective transfer in defining how learners apply their past language skills. Their study shows the ways that past linguistic exposure impacts the process of learning new languages. Examining these prior studies offers an outline of ideas, methods, and evidence that help guide the development and execution of our research.

Methods

To investigate whether Spanish heritage speakers find it easier to acquire a third language (L3) within the same language family, we conducted a phonetics-focused study comparing participants learning French, a Romance language, and Korean, a Koreanic language. In the process of gathering participants, we reached out to professors and teaching assistants in the French and Korean departments within institutions such as UCLA who distributed our survey to Korean and French learners in their class who were Spanish heritage speakers. Participants included a total of eleven participants, six Spanish heritage speakers acquiring French and five Spanish heritage speakers acquiring Korean, all at beginner or intermediate proficiency levels. Due to our limited time and Thanksgiving break overlapping with our outreach, we decided to reach out to the Spanish club and extended our research group to include intermediate speakers; this gave us the last few participants we needed. The Google form starts with qualitative questions to gather data on the participant’s proficiency and the languages they speak. Knowing the participants’ proficiency in potential languages allowed the ability to exclude participants that would result in confounding data.

We tested our hypothesis by experimenting using a listening comprehension methodology that measures the accuracy of a participant’s phonetic perception of sounds in their third acquired language of French or Korean. Consequently, the focus of this experiment was phonetics, and as a result, we examined how vowel perception has the potential to be under the influence of proximity among linguistic families. We utilized this methodology to compare the accuracy percentage of French, a language in the same Romance language family as Spanish, and Korean, a language from the Koreanic language family that is unrelated to Spanish. In the experiment, the participants completed a listening comprehension task by listening to recorded words from their respective L3s. Data was collected via Google Forms, with audio stimuli being produced through IPA reader for our French survey and recorded by a native Korean speaker for the Korean survey. The French survey tested five words and the Korean survey tested seven words, such as “dans” for French and “바다” for Korean, both containing the same shared vowel with Spanish, /a/. The participants were then instructed to manually type in what sounds they heard and were given a list of all vowels in their respective languages to choose from. During the listening comprehension task, the participants identified vowel sounds in the French or Korean words to assess their ability to identify the same vowel sounds in their respective L3. The vowels analyzed include shared sounds such as /a/, /i/, /e/, and /o/ for French and Spanish, and Korean vowels such as /a/, /u/ and /o/.

After collecting responses from respective participants, responses were analyzed for accuracy to determine whether linguistic proximity between L1 and L3 facilitated phonetic perception. By calculating the ratio of accurately identified vowels to the total number of questions and multiplying the quotient by one hundred, we were able to calculate the accuracy percentage for each survey. To compare the average accuracy between the French and Korean surveys, we took the mean scores of both surveys, accounting for all participants. Depending on the comparative accuracy percentages, we sought to assess whether linguistic proximity, such as French and Spanish in the Romance language family, provided an advantage over unrelated language pairs, such as Spanish and Korean from the Koreanic language family.

Results and Analysis

Analysis was conducted based on the participants’ accuracy in the listening comprehension task. We were able to recruit 11 participants: six French L3 learners and 5 Korean L3 learners. Surprisingly, we found that the results did not confirm our hypothesis, which stated that learning a third language within the same family is simpler and quicker for heritage Spanish speakers. Instead, we found that Korean learners performed with slightly better margins on the phonetic vowel listening task, acquiring an 87.5% accuracy, and French learners acquired an 83.3% accuracy overall. Contrary to our predictions and proposed hypothesis, these results indicate no notable advantage was observed on the impact of one’s heritage language on their L3 acquisition. The participants showed no significant benefit in their L3 acquisition of French or Korean by having acquired Spanish as a heritage language. Our intuition was that the participants would do better with French than Korean given that Spanish and French are derived from the same language family.

However, it is difficult to generalize these results to a larger population because the study did encounter setbacks that may have affected our findings. First and foremost, we had a very limited sample size. At the time of this study, we were able to reach out to various beginner and intermediate-level language courses at UCLA in French and Korean for participants, but given the specificity of our subject requirements, it was difficult to find individuals who qualified for the study. Second, we were under strict time constraints. While most research projects are able to go on for an indefinite amount of time, we had a little under 10 weeks to research and design our study, create the experiment, find participants, and run data analysis. Lastly, we were unable to use our preferred experimental software, Gorilla, due to lack of funding, so we opted for a Google form survey.

Originally we were inspired to study the connection between learning a new language and a person’s heritage language. We chose Spanish speakers in hopes of broadening our sample size. Attending university in Los Angeles, we knew we would have the most luck finding Spanish heritage speakers and having access to UCLA’s diverse student body aided in our search. In the future, we would like to examine more language families and increase our sample size to acquire a larger amount of data. We would also like to extend our research from its current focus on phonetics and explore the impact of heritage languages on the syntax, morphology, or pragmatics of other acquired languages. We felt phonetics was the best place to start because we knew we would eventually be reaching out to introductory-level language courses in French and Korean for volunteers. Phonetics is the basis of all languages and is the focus of most beginner classes, so for this reason, we chose to test the participants utilizing vowels. This guaranteed the participants had been properly exposed to sounds similar to our stimuli. While our results were not what was expected, in the future, we would like to see if these same results are consistent for morphology, syntax, pragmatics, or within other language families. To expand the study, it would be beneficial to expand syntactic data by testing the participants with questions that focus on grammar. This would allow us to see if differing grammar rules has an affect on the participants’ performance. Languages can be from the same word family and have a different word order. Some languages can even have more than one word order. Would knowing Spanish be beneficial or would it lead to more error if the participant is learning a language with a completely different word order. Similarly, morphology could be used to further the study and test if the relationship is different for morphology versus phonetics and syntax. The participants could be tested on affixes across languages. Many suffixes and prefixes are borrowed from other languages and so both French and Korean participants could be asked to identify affixes that are found in Spanish and in French and Korean. The results could show us if knowing Spanish is beneficial to identifying definitions even when the root of the word is not found in Spanish.

Visuals for Results Section:

Figure 1: Participants rated their proficiency in Spanish

Figure 2: Participants rated their proficiency in Spanish

Figure 3: Participants identified the letters read out to them through an audio

Figure 4: Participants identified the letters read out to them through an audio

Appendix

Korean WordsExplanationFrench WordsExplanation
1.  사람 [ˈsʰa̠(ː)ɾa̠m]1.  Connecting the phoneme /a/ to the new character ‘아’Toute [tut]In testing the phoneme /u/ and whether learners can connect it to the orthographic element ‘ou’ Different from Spanish ‘u’
2.  바다 [pa̠da̠] 2. Dans [dɑn̚]In testing the phoneme /ɑ/ and whether learners can connect it to the orthographic element ‘a’ No such phoneme in Spanish
3.  자다 [t͡ɕa̠da̠] 3. Mais [mɛ]In testing the phoneme /ɛ/ and whether learners can connect it to the orthographic element ‘ai’ Different from Spanish representation ‘e’
4.  모자 [mo̞d͡ʑa̠]1.  Connecting the phoneme /o/ to a new character ‘오4.  Va [va]In testing the phoneme /a/ and whether learners can connect it to the orthographic element ‘a’ Control case
5.  도로 [ˈto̞(ː)ɾo̞] 5. Été [ete]In testing the phoneme /e/ and whether learners can connect it to the orthographic element ‘e’ Control case
6.  눈 [nun]1.  Connecting the phoneme /u/ to a new character ‘우’  
7.  구름 [kuɾɯm]   

Discussion and Conclusion

Looking forward, the importance of the information that this study can provide should not be overlooked. Observing potential advantages to knowing one language as an HL and learning a new one can lead to important social implications. Mainly, social stigma about speaking languages can be curbed and lessened. Much like Israel Jesus in the weekly Subtitle podcast episode titled “From linguistic shame to pride” (Spotify Studios 2023), language pride can lead to very big differences in someone’s life. Going from having shame in speaking a language to having the pride to use it to help save someone’s life (like in a medical translation setting for Israel). Give the podcast a listen to hear his story! It provides deep insight into the struggles of speaking a language considered “lesser than” or stereotyped and how knowing that that language is useful in some way can help to overcome stigma and self consciousness. This is the essence of what we hope to investigate.

References

Deng, J. (2022, December 30). The Teaching and Learning of Third Tone Sandhi: L2- and Heritage-Learners of Mandarin Chinese in Canadian University Classes. International Journal of Chinese Language Teaching. https://www.clt-international.org/journal/details/info/7ODEu8MzEx/The- Teaching-and-Learning-of-Third-Tone-Sandhi:-L2–and-Heritage-Learners-of-Mandarin-Chinese-in- Canadian-University-Classes

Hopp, H. (2014,January 18). Cross-linguistic influence in the child’s third language acquisition of grammar: Sentence comprehension and production among Turkish-German and German learners of English. Sage Journals. https://journals.sagepub.com/doi/full/10.1177/1367006917752523

Lorenz, E. (2018, August 13). Cross-Linguistic Influence in Unbalanced Bilingual Heritage Speakers on Subsequent Language Acquisition: Evidence from Pronominal Object Placement in Ditransitive Clauses. Sage Journals .https://journals.sagepub.com/doi/full/10.1177/1367006918791296

Mayr, R. (2016, October 16). Inter-generational transmission in a minority language setting: Stop consonant production by Bangladeshi heritage children and adults. Sage Journals. https://journals.sagepub.com/doi/full/10.1177/1367006916672590

Montrul, S. (2010, July 3). Dominant language transfer in adult second language learners and heritage speakers. JSTOR. https://www.jstor.org/stable/43103834?sid=primo&seq=7

Westergaard, M. (2016, May 19). Crosslinguistic influence in the acquisition of a third language: The Linguistic Proximity Model. Sage Journals. https://journals.sagepub.com/doi/10.1177/1367006916648859

Machová, L. (2019, February). The secrets of learning a new language [Video]. TED. https://www.ted.com/talks/lydia_machova_the_secrets_of_learning_a_new_language?subtitle=en

Spotify Studios. (2023). From linguistic shame to pride [Audio podcast episode]. In Subtitle. Spotify. https://open.spotify.com/episode/778VXYt9XxDUUzgKLMzQL6?si=6df3f3ab0f0c454e

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Navigating Bilingual Realities: Mandarin-English Code-Switching

Qianwei Tao, Yinlin Xie, Zhifei Lei, and Yifan Yin

What makes bilinguals switch between languages mid-sentence, seemingly effortlessly? This captivating phenomenon, called code-switching, reflects the adaptability of bilingual communication. In our study, we focused on Mandarin-English bilinguals to explore how mixed-language prompts and formality levels influence their linguistic choices. Through analyzing responses from 20 participants aged 18 to 25, we found an unexpected pattern: formal prompts, traditionally thought to discourage language mixing, elicited higher rates of code-switching compared to informal ones. This discovery challenges long-held assumptions and shows the nuanced relationship between language, social context, and communication. By exploring further the structured nature of formal prompts and their impact on bilingual expression, this study shows how bilinguals use code-switching as a tool for communication. These findings open a window into the interaction of language and context, offering new perspectives on how bilinguals navigate their communication.

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Introduction and Background

Language functions as more than just a tool for communication; it mirrors our social and cognitive realities. For bilinguals, this reflection shows in the phenomenon of code-switching, specifically intra-sensational code-switching, the act of alternating between two languages within a single sentence. This dynamic process is influenced by numerous factors, including context and language dominance. Language dominance also determines how fluently individuals switch between languages, and this is defined as the relative proficiency or preference for one language over another (Deuchar, 2020). For example, research shows that bilinguals frequently code-switch into their dominant language in casual settings but adhere to monolingual norms in formal contexts (Muysken, 2000). This shows that code-switching is not only a linguistic skill but also a social strategy that allows bilinguals to adapt seamlessly to diverse social cues and contexts (Green, 1998). Regarding these ideas, our study addresses the main research question: How do mixed-language prompts and varying levels of formality influence code-switching behavior in Mandarin-English bilinguals?

Research has shown that the context of communication heavily influences code-switching behavior. Formal settings often promote monolingual language use, emphasizing precision and adherence to linguistic norms (Myers-Scotton, 1993). On the other hand, informal contexts allow greater flexibility, enabling bilinguals to switch languages more freely (Deuchar, 2020). However, existing studies have not sufficiently explored how bilinguals respond to formal prompts containing mixed-language elements (Deuchar, 2020). This gap in the literature leaves unanswered questions about the nuanced interplay between linguistic input and social contexts.

Mandarin-English bilinguals provide us with an especially intriguing population for examining this phenomenon in this study. These bilinguals frequently engage in code-switching due to its structural and cultural contrasts between Mandarin and English (Green & Wei, 2014). This study tests the hypothesis that informal prompts with mixed-language elements will elicit higher rates of code-switching compared to formal prompts. We predict that Mandarin-English bilinguals will demonstrate strategies for adapting their writing to fit in contextual demands, with their switching behavior shaped by the linguistic input they take. Though there is extensive existing research, gaps remain in understanding how linguistic input and contextual factors interact to shape bilingual communication. Existing studies have focused on informal contexts or monolingual prompts, leaving questions about formal settings and mixed-language input underexplored (Deuchar, 2020). Addressing these gaps provides an opportunity to deepen our understanding of bilingual communication as a nuanced and adaptive process. Code-switching is not merely a linguistic phenomenon but a sophisticated strategy for navigating complex communication landscapes. It highlights the adaptability of bilinguals in managing diverse linguistic and social demands, which offers valuable insights into the interplay of language, context, and culture.

Methods

This study examined how Mandarin-English bilinguals respond to linguistic prompts varying in level of code-switching and formality. We recruited 20 participants aged 18-25, all Mandarin-dominant bilinguals with English as their second language. Participants were selected based on their self-reported regular engagement in code-switching to ensure appropriate alignment with the experimental tasks. Participants completed linguistic tasks designed to analyze their code-switching behavior. The tasks involved responding to prompts that differed in two key aspects: language composition (monolingual prompts [CS-] versus mixed-language prompts [CS+]) and context (formal, semi-formal, and informal settings). These variables were chosen to explore how prompt design and contextual formality interact to influence code-switching patterns. This approach allowed us to observe intra-sentential code-switching, where participants alternated between Mandarin and English within a single sentence, one of the most cognitively demanding forms of code-switching (Green & Wei, 2014).

The data collection of the study focused on the frequency and type of code-switching, with responses categorized based on their linguistic composition and analyzed for patterns across different conditions. To describe intra-sentential code-switching, we utilized two categories other than Monolingual condition. One is multiple-word insertion, which involves inserting multiple words or phrases from one language into the grammatical structure of another language within a sentence (Muysken, 2000). We also incorporate the alternational code-switching that has more extensive switching within a single sentence, involving longer phrases or clauses (Dulm, 2007). This categorization allowed for a nuanced analysis of the participants’ code-switching behavior in response to the linguistic prompts. Participants are told that they can respond in any language they feel most natural to answer. The categorized prompt of the survey is indicated below:

Group 1: CS Level Condition

  1. Monolingual/Informal:
    • What’s the most random thing that’s happened to you this week?
  2. Alternational Code-switching/Informal:
  3. ○最近你发现啥新地方超好吃的, like legit worth recommending?
    1. ○(What new places have you discovered recently that are super delicious?)
  4. Multiple-word Insertion/Informal:
    1. 你最近有没有吃到什么literally超赞的地方, like那种vibe很chill而且超好吃的?
      1. (Have you eaten at any literally amazing places recently, like places with a chill vibe and super delicious food?)

Group 2: Formality Level Condition

  1. Formal Prompt/Mixed-language (CS+):
    1. 请分享一个 significant challenge in your academic journey and how you overcame it.
      1. (Please share a significant challenge in your academic journey and how you overcame it.)
  2. Semi-Formal Prompt/Mixed-language (CS+):
    1. 跟我们说说你最喜欢的hobby, and how it fits into your daily life.
      1. (Please tell us your favorite hobby, and how it fits into your daily life.)
  3. Informal Prompt/Mixed-language (CS+):
    1. 一个朋友发消息问你 “你周末打算干嘛? Any fun plans?” 你会怎么回答。
      1. (A friend texted you “What are you up to this weekend? Any fun plans? What would you reply? ”)

These categories align with the matrix language model and provide a clearer understanding of the extent of language mixing within a single sentence (Muysken, 2000; Dulm, 2007). Graphs summarizing the results were labeled with condition names, like “Figure 1 Code-Switching Frequency by Level of Code Switching” and “Figure 2: Code-Switching Frequency by Context Formality.” Also, graphs are titled as “Group 1: CS Level Condition”, and “Group 2: Formality Level Condition.” This ensured that findings were visually intuitive and accessible. We also framed our participant group as homogeneous in terms of their language dominance and bilingual proficiency to confirm group similarities. By aligning terminology with the matrix language model, we clarified “insertion” as the process of embedding words from one language into the grammatical structure of another (Muysken, 2000). Recruitment was conducted through social media platforms like Instagram and WeChat. A pre-survey assessed participants’ language dominance, proficiency, and code-switching habits. This survey included demographic questions and self-assessments of fluency and language usage patterns in formal and informal contexts. This streamlined methodology can effectively explore how linguistic prompts and context influence bilingual communication.

Results and Analysis

The experiment results are obtained from 20 participants, aged 18 years old to 25 years old. Male participants significantly dominate the sample, being 66.7%, while female participants take up to 33.3%. Most of the participants are currently enrolled in college or holding a bachelor’s degree. All participants share an advanced proficiency in their native language, Mandarin, and a moderate fluency in their second language, English. Based on the pre-survey scores, apparently there is a strong agreement among the participants that mixing languages is natural bilingual practice. They exhibit a tendency to mix languages more frequently in informal settings, such as being with family or friends. Meanwhile, they mix languages moderately in formal settings, usually for academic or professional purposes. They all show a high level of comfort using mixed language in online environments.

Survey 1 contains informal scenarios with three types of prompts: monolingual code-switching (CS-): e.g. “What’s the most random thing that’s happened to you this week?”; alternational code-switching (CS+) prompts: e.g. “最近你发现啥新地方超好吃的, like legit worth recommending? (What new places have you discovered recently that are super delicious?)”; multiple-word insertion prompts: e.g. “你最近有没有吃到什么literally超赞的地方, like那种 vibe很chill而且超好吃的? (Have you eaten at any literally amazing places recently, like places with a chill vibe and super delicious food?) ”. Results show that monolingual CS- prompts are the least likely to evoke code-switching responses (10%), and alternational CS+ ones are moderately likely to trigger code-switching (60%), yet multiple-word insertion ones are the most likely to prompt code-switching responses (70%).

In the graph below, the x-axis represents different levels of CS, while the y-axis represents the frequency of CS occurring in percentage. The overall graph shows a positive trend among the three types of prompts, indicating a correlation that the more insertions present within a sentence, the more likely it is for speakers to code-switch. These findings suggest that the structure and complexity of the prompt can be impactful to the frequency of code-switching. In informal contexts, prompts with more embedded English words facilitate code-switching more effectively.

Figure 1.Code-Switching Frequency by Level of Code Switching

Survey 2 focuses solely on CS+ prompts across formal, semi-formal, and informal contexts. Unexpectedly, formal prompts elicit a higher frequency of code-switching (60%) compared to semi-formal (30%) and informal (30%) contexts. In the graph below, the x-axis represents different levels of formality, whereas the y-axis represents the frequency of CS occurring in percentage. The graph exhibits a negative trend overall, suggesting that the less formal the setting is, the less likely speakers would code-switch. This reversal of the initial formality hypothesis indicates baseline behaviors among participants. To exemplify, a formal prompt such as “请分享一个 significant challenge in your academic journey and how you overcame it.

(Please share a significant challenge in your academic journey and how you overcame it.)”, contains structured content and professional diction, thus encouraging interactive engagement and bilingual expression. Conversely, informal prompts like “最近你发现啥新地方超好吃的, like legit worth recommending? (What new places have you discovered recently that are super delicious?)” triggers monolingual Mandarin responses with rare occurrences of code-switching. This implies that participants will regard informal prompts as less demanding compared to formal counterparts, thus less likely to code-switch.

Figure 2. Code-Switching Frequency by Context Formality

The higher likelihood to code-switching in formal contexts contradicts the hypothesis that informality would raise the chances of language mixing. There are a few plausible explanations for this unconventional phenomenon.

  1. Baseline Behavior: participants interpret informality as less linguistically demanding than formality, meaning that they might use L1 exclusively, rather than spending more cognitive effort to insert L2 components into casual conversations.
  2. Prompt Design: formal prompts consist of naturally embedded English components, increasing the likelihood of participants to incorporate English into their responses. It explains how code-switching behavior of participants heavily rely on the design of prompts.
  3. Perceived Social Norms: speakers tend to showcase their bilingual ability more frequently in formal settings because professionalism is commonly associated with an advanced bilingual proficiency. To align with this social perception, they are more likely to engage in code-switching to demonstrate their fluency and competence.

These findings offer valuable insights for the field of bilingualism and in particular, code-switching. However, further research is needed to examine how bilingual behaviors can be shaped by sociolinguistic and psycholinguistic factors, and whether these linguistic trends are consistent among bilinguals with varying degrees of proficiency, or with different language combinations.

Discussion and Conclusion

In conclusion, this study provides a deeper version of the relationship between contexts in bilingual communication based on previous research on code-switching in bilingual speakers, focusing on the code-switching behavior of Mandarin-English bilinguals. Surprisingly, the findings differ from traditional assumptions and the formal hypotheses: code-switching is more likely to occur for bilinguals when combined with mixed-language prompts (CS+) in formal contexts than in informal contexts. This untraditional result challenges the long-held view that the cognitive demands of processing mixed-language input and the structure and guidance in formal contexts actually encourage bilinguals to use code-switching strategically for expression and communication.

This encouragement would lead bilinguals to utilize code-switching as a tool for conscious and strategic communication, which is consistent with the theory that bilinguals adapt their language to specific contexts, and that prompts give specific language expressive demands to motivate bilinguals to higher attentional control to help them integrate the two languages for complex articulations. In addition, the structure and complexity of the prompts can be overwhelmingly significant in affecting the frequency of code-switching behaviors. Mixed-language prompts (CS+) consistently lead to code-switching expressions, which is consistent with Deuchar’s (2020) token modeling theory that prompts can motivate bilinguals to activate both languages simultaneously to communicate, making code-switching a natural and effective way of communicating, which proves the theory that code-switching is not a spontaneous or arbitrary process but rather a deliberate linguistic strategy used to carry out a specific conversational goal.

Although the study presents different challenges, certain limitations exist. The specific participant demographics and small sample size limit the results of the study to a great extent. Specific language choices are also a limitation, and different language choices in the same study could have led to variations in results. In the future, the choice of greater linguistic diversity, an unspecified participant population, and a larger sample size are key factors for obtaining further validation and more comprehensive experimental results. However, other factors, such as cultural diversity, language ability and individual differences, may also influence the results, which will require future researchers to make more careful choices about the conditions of their experiments.

Two Relevant Talk/Podcast

  1. TED Talk: “Code-Switching to Navigate the World Around Us” by Jaellin King

King (2019) explores how different languages can positively impact how people navigate their surroundings. She mainly discusses the importance of being fluent in more than one standard of language to communicate effectively within diverse communities in this TED Talk. This idea aligns with our study’s focus on how bilinguals respond to linguistic prompts in various contexts, particularly the formal, semi-formal, and informal settings examined in the research. King’s idea also aligns with Muyskens’ article, supporting that the patterns and frequency of code switching can be influenced by different context and cues (Muysken, 2000).

  • Podcast: “Code-switching as a School Strategy” by IDRA

This podcast episode delves into how code-switching can be used in educational settings to

create more inclusive environments for students. It discusses building an inclusive curriculum and how to use code-switching to better support students. This is related to Green’s article that Code-switching is used by bilinguals as a social strategy that allows them to navigate in different contexts (Green, 1998).

References

Deuchar, M. (2020). Code-switching in linguistics: A position paper. Languages, 5(2), 22. https://doi.org/10.3390/languages5020022

Dulm, O. V. (2007). The grammar of English-Afrikaans code switching: A feature checking account. LOT.

GREEN, D. W. (1998). Mental control of the bilingual lexico-semantic system. Bilingualism (Cambridge, England), 1(2), 67–81. https://doi.org/10.1017/S1366728998000133

Green, D. W., & Wei, L. (2014). A control process model of code-switching. Language, Cognition and Neuroscience, 29(4), 499-511.

Green, D. W., & Wei, L. (2014). A control process model of code-switching. Language, Cognition and Neuroscience, 29(4), 499–511. https://doi.org/10.1080/23273798.2014.882515

IDRA. (2019, July 1). Code-switching as a school strategy – Podcast episode 192. https://www.idra.org/resource-center/code-switching-as-a-school-strategy-podcast-episod e-192/

King, J. (2019, November). Code-switching to navigate the world around us [Video]. TEDx Conferences. https://www.ted.com/talks/jaellin_king_code_switching_to_navigate_the_world_around_ us

Muysken, P. (2000). Bilingual speech: A typology of code-mixing. Cambridge University Press. Myers-Scotton, C. (1993). Social motivations for codeswitching : evidence from Africa / Carol

Myers-Scotton. Oxford: Clarendon Press. Yow, W. Q., Tan, J. S. H., & Flynn, S. (2018). Code-switching as a marker of linguistic competence in bilingual children. Bilingualism: Language and Cognition, 21(5), 1075-1090. https://doi.org/10.1017/S1366728918000078

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The Effect of Code-Switching on Voice Onset Time (VOT) in Spanish-English Bilinguals

Miroslava Albiter, Caitlin Morlett, Renee Ma, Jaquelin Trujillo, and Zirui(Ray)

Have you ever heard your friend or family speak two languages in one phrase? Have you ever spoken two languages in a sentence? We look deeper into how code-switching affects phonological convergence, specifically in Spanish-English bilinguals. A key phonological difference between English and Spanish is the articulation of word-initial voiceless stops such as /p/, /t/, and /k/. Therefore, we specifically analyzed how the Voiced Time Onset (VOT) measures of Spanish-English bilinguals are affected by code-switching between Spanish and English. Sixteen English-Spanish bilinguals were recorded and asked to read aloud the Rainbow passage, a passage with English sentences, Spanish sentences, and code-switched English-Spanish sentences. PRAAT was used to measure the participants’ VOTs to compare the differences to a baseline VOT measure of monolingual English and Spanish speakers (Castañeda Vicente, 1986; Lisker & Abramson, 1964).

After data collection and analysis, we discovered that both VOTs of English and Spanish were lengthened during code-switching, albeit for different reasons. As Spanish VOT extended due to phonological convergence, English VOT also unexpectedly extended. We observed evidence for hyper-articulation, which can further explain our conclusion. However, limitations are reckoned with, and thus, fields of phonological change within code-switched contexts are explored.

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Introduction and Background

In this article, we investigated code-switching in English-Spanish bilingual college students, focusing on their phonological change along with the process of code-switching through Voice Onset Time. Code-switching “is a practice common among bilinguals whereby speakers use both languages in a single utterance” (Balukas & Koops, 2015). We will analyze whether English-Spanish bilingual college students demonstrate phonological convergence of VOT in code-switching sentences. The age range of the 16 tested participants varies, with 14 being 20 years old and the other two between 40 and 50 years old. After collecting data, we examined the Voice Onset Time (VOT) in different circumstances and the subsequent phonological convergence in English-Spanish code-switched sentences.

According to previous research, English monolingual speakers typically produce a longer VOT of word-initial voiceless stops than Spanish monolingual speakers (Balukas & Koops, 2015). Samples from bilingual participants were collected and analyzed using Praat, with a particular focus on VOT changes and the evidence of subsequent phonological convergence. As such, we are investigating a potential phenomenon wherein the English VOT is observed to shorten while the Spanish VOT lengthens in English-Spanish code-switched sentences. This dynamic interaction may be further interpreted as evidence of phonological convergence, reflecting an underlying adjustment mechanism within bilingual speech production systems. Due to the lack of ready access to true monolingual speakers in the LA area, we will use data from the BYU Scholars Archive to compare the VOT of our bilingual speakers to the average VOT for /p/, /t/, and /k/ in both English and Spanish. In the BYU Scholars Archive, the Spanish baseline was recorded at the University of Barcelona in 1986 and was taken from 10 monolingual Spanish speakers (Castañeda Vicente, 1986). The English baseline in the archive was recorded at the University of Pennsylvania in 1964 based on 4 American monolingual English speakers (Lisker & Abramson, 1964).

Figure 1 – Chart from BYU Scholars Archive showing the average VOT is ms for English bilinguals and Spanish bilinguals

Phonological properties, including VOTs, can be differentiated across various dialects, even within the same language. In this research, our participants predominantly speak LAVS (Los Angeles Vernacular Spanish), while three speak the Castellano dialect.

In this study, we will investigate whether code-switching influences VOT in English-Spanish bilingual speakers. Testing the specific phonological changes in VOTs in English and Spanish during code-switching. It finally aims to detect the phonological convergence during code-switching in English-Spanish bilinguals. Our hypotheses of VOT and phonological convergence are as follows:

  1. English-Spanish bilingual speakers will shorten English VOT and lengthen Spanish VOT compared to true monolingual speakers of each respective language.
  2. If the speaker’s L1 is English and their L2 is Spanish, we expect the VOT for Spanish /p/, /t/, and /k/ to be longer than Spanish monolingual speakers. We also expect their English VOT for /p/, /t/, and /k/ to reflect the VOT of monolingual English speakers.
  3. If the speaker’s L1 is Spanish and their L2 is English, we expect the VOT for English /p/, /t/, and /k/ to be shorter than English monolingual speakers. We would also expect their Spanish VOT for /p/, /t/, and /k/ to reflect the VOT of monolingual Spanish speakers.

If a participant has been discouraged from speaking Spanglish, they will be more likely to have longer VOT in Spanish despite differences in their L1 or L2.

To clarify related concepts, VOT is “the temporal relationship between laryngeal pulsing and the onset of consonant release” (Molfese & Narter, 1997). Phonological convergence, on the other hand, refers to the process by which speakers in a communicative interaction adjust their phonological patterns—such as pronunciation, intonation, or rhythm—towards one another. A key phonological distinction between English and Spanish arises primarily in articulating word-initial voiceless stops, namely /p/, /t/, and /k/. Positive VOT, or aspiration, is characterized by a puff of air following the release of the stop.

A phonological rule of English specifies that word-initial voiceless stops are aspirated or have a positive VOT. Word-initial voiceless stops in Spanish are typically not aspirated or aspirated, much less than English word-initial voiceless stops (Piccinini & Arvaniti, 2015). We will explore Voice Onset Time in code-switching contexts. Code-switching “is a practice common among bilinguals whereby speakers use both languages in a single utterance” (Balukas & Koops, 2015). We will analyze whether English-Spanish bilingual college students demonstrate phonological convergence of VOT in code-switching sentences.

Methods

We will first have all participants complete the demographic and self-report questionnaire about their linguistic background. The questionnaire will include information about their L1 and L2, how often they code-switch, their proficiency in speaking and reading both languages and if they speak any other languages. Lastly, we will include sociocultural questions about their language use, including how positively or negatively they feel about speaking Spanglish and if they have ever been discouraged from speaking Spanglish.

The participants will read “The Rainbow Passage,” a context that includes a mix of English-only sentences, Spanish-only sentences, and sentences that switch from English to Spanish or Spanish to English. We will account for individual idiosyncrasies while striving to derive principles that are as generalizable as possible. The participants will read the following paragraph adapted from the Rainbow Passage with pre-written code-switched sentences:

When the kind sunlight strikes cold raindrops in the air, they act as a prism and form a rainbow. El arcoiris divide la luz blanca en muchos colores hermosos. Estos toman la forma de un arco tan largo, with its path high above, and its two ends apparently beyond the horizon. There is, according to legend, a boiling pot of gold at one end. People look, pero nadie lo encuentra. Cuando un hombre busca algo más allá de su alcance, sus amigos pueden decir que está buscando la olla de oro al final del arcoíris. Throughout the centuries, people have explained the rainbow in various ways. A recording device will be used to record samples of participants using Praat to measure the phonetic output of the individuals and the length of VOT across all conditions. The English words from the Rainbow Passage that we will analyze include kind, cold, two, to, pot, and people. The Spanish words from the Rainbow Passage that we will be analyzing include colores, toman, tan, pero, cuando, and pueden.

Results and Analysis

Several group members contacted qualified bilingual participants and provided access to the prerequisite questionnaire. After collecting basic information about their first language acquisition (FLA) and second language acquisition (SLA) or second language learning (SLL), we distributed the altered Rainbow Passage to participants, ensuring that the recordings of their utterances were clear and suitable for further analysis. We then reviewed all recordings for quality and completeness before forwarding them to those responsible for data analysis. Audio recordings were collected and analyzed using Praat to find the VOT length. The data collected using Praat for each of the 16 participants is grouped into different categories in order to test the following hypotheses.

  1. Average bilingual /p/, /t/, /k/ VOT compared to monolingual /p/, /t/, /k/ VOT (BYU)
  2. Group English L1 speakers /p/, /t/, /k/ VOT and compare to Spanish L1 speakers /p/, /t/, /k/ VOT
  3. The average /p/, /t/, and /k/ VOT for both languages was based on whether or not they were discouraged from speaking Spanglish.

Based on our data grouping, we discovered that our first hypothesis was false because the English VOT mean values for all 16 of our participants (/p/ 85 ms) (/t/ 75 ms) (/k/ 86 ms) were longer than our baseline measurements. Our Spanish voiceless stop mean values based on 16 participants (/p/ 22 ms) (/t/ 75 ms) (/k/ 27 ms) had a /p/ and /t/ value that was longer than the baseline measures, but the /k/ mean was similar to the baseline data.

Figures 2 and 3—The graph shows the mean VOT in milliseconds for all 16 participants. Figure 2 displays the English VOT values for /p/ (blue), /t/ (red), and /k/ (yellow). Figure 3 shows the Spanish VOT values for /p/ (blue), /t/ (red), and /k/ (yellow). 

We found our second hypothesis partially correct because our Spanish VOT was longer than the baseline data, but our English VOT was also longer than the English baseline. Our English L1 Spanish Voiceless mean VOT values (/p/ 28 ms) (/t/ 22 ms) (/k/ 72 ms) were longer than the VOT baseline data collected from Spanish monolinguals. Our English L1 English mean VOT values were similarly longer than those of English monolingual speakers in the baseline data.

Figures 4 and 5 – The graph shows the mean VOT in milliseconds for all participants with English as their first language. Figure 4 shows the English VOT values for /p/ (blue), /t/ (red), and /k/ (yellow). Figure 5 shows the Spanish VOT values for /p/ (blue), /t/ (red), and /k/ (yellow).

We discovered that our Spanish VOT was longer than our baseline for the /k/ voiceless stop, partially supporting our third hypothesis. Our Spanish L1 English mean VOT (/p/ 51 ms), (/t/ 63 ms), (/k/ 72 ms) was shorter than our baseline, as expected. When we looked at our Spanish L1 Spanish, mean VOT (/p/ 18 ms), (/t/ 18 ms), and (/k/ 27 ms), we discovered that the /p/ and /t/ mean VOT values were longer than the baseline, while the /k/ mean VOT value was identical to the baseline value.

Figures 6 and 7 – The graph shows the English VOT values for /p/ (blue), /t/ (red), and /k/ (yellow). Figures 6 and 7 show the mean VOT in milliseconds for all participants whose first language was Spanish. The Spanish VOT values for /p/ (blue), /t/ (red), and /k/ (yellow) are shown in Figure 6.

Since the participants who were discouraged from speaking Spanish had a lower VOT than those who were encouraged to speak Spanish, our fourth hypothesis was false. In comparison to our encouraged Spanish mean VOT, which is (/p/ 24 ms) (/t/ 24 ms) (/k/ 28 ms), our discouraged Spanish mean VOT was (/p/ 18 ms) (/t/ 18 ms) (/k/ 28 ms).

Figures 8 and 9—The graph shows the average VOT in milliseconds for each of the 16 participants according to whether they had been encouraged to speak Spanglish. The mean VOT in ms for the /p/, /t/, and /k/ values for the participants who received encouragement is displayed in Figure 8. The mean VOT in ms for the discouraged participants’/p/, /t/, and /k/ values are displayed in Figure 9.

Figures 10 and 11 – Both are screenshots of the Praat spectrograms of one of our participants. The VOT of the participant who produced the [t] in the word “toman” is displayed in red in Figure 10 (left). The VOT of the participant who produced the [tʰ] in the word “to” is displayed in red in Figure 11 (right). Speaking Spanglish has been discouraged for this individual, whose first language is Spanish.

Figures 12 and 13 –  Both are screenshots of the Praat spectrograms of one of our participants. The VOT of the participant who produced the [p] in the word “pero” is displayed in red in Figure 12 (left). The VOT of the participant who produced the [pʰ] in the word “people” is displayed in red in Figure 13 (right). Speaking Spanglish has been discouraged for this individual, whose first language is Spanish.

Figures 14 and 15 –  Both are screenshots of the Praat spectrograms of one of our participants. The VOT of the person who produced the [k] in the word “colores” is displayed in red in Figure 14 (left). The VOT of the person who produced the [kʰ] in the word “kind” is displayed in red in Figure 15 (right). Speaking Spanglish has been discouraged for this individual, whose first language is Spanish.

Discussion and Conclusion

This research aims to contribute to understanding phonetic changes during code-switching, focusing on the syllables /p/, /t/, and /k/. The findings indicate that, in addition to phonological changes influenced by language-specific properties, hyper-articulation during the experimental process can also impact the results. Notably, the VOTs of both English and Spanish were lengthened, albeit for different reasons. While previous studies suggested that English VOT should remain stable, the observed lengthening may be attributed to hyper-articulation. This phenomenon occurs when participants consciously articulate more clearly to facilitate phonetic analysis, particularly when instructed to produce distinct utterances for experimental recording. The results aligned with some of our hypotheses, though some biases were observed. Further analysis is required to identify academically sound explanations for these findings.

Due to the difference in language properties, the Spanish VOT is lengthened as predicted. Spanish generally exhibits shorter VOT than English. During code-switching between English and Spanish, the VOT of Spanish syllables was observed to be longer than that of monolingual Spanish speakers, suggesting the occurrence of phonological convergence. However, the lengthened English VOT needed to be accounted for in the hypotheses regarding phonological convergence, necessitating further exploration for alternative explanations.

Based on one of our references (Kasia Muldner,2017), English VOT during code-switching is nearly identical to monolingual speakers, which can be attributed to differences in language-specific characteristics. Consequently, English undergoes minimal phonological changes during code-switching. Our hypotheses align with previous studies, suggesting that despite minor variations, English VOT remains nearly identical to that of monolingual English speakers. However, this experiment’s data showed opposite conclusions, forging us to discover more reliable explanations.

Overall, all VOT measures, except for the Spanish /k/, did not reflect our true monolingual English and Spanish speakers. Baseline data demonstrated an increase in VOT data as the place of articulation was placed further back in the vocal cavity. The /p/ VOT was the shortest, next was /t/ VOT, and the longest was the /k/ VOT in both English and Spanish. Our participants produced a similar VOT for all the English stops (around 80 ms) and all Spanish stops (around 23 ms) These findings suggest that bilingual speakers may default to one length of VOT regardless of the place of articulation, whereas monolingual speakers produce a different VOT length for each stop consonant. Despite previous research, this provides evidence that bilinguals differ in VOT production from monolinguals. 

Another interesting finding was hyper-articulation in our sample, which was characterized by more distinct and easily recognizable pronunciations. This phenomenon is hypothesized to have occurred because participants were instructed to produce clear recordings for subsequent analysis using professional phonetic tools (PRAAT), inadvertently creating a more demanding articulatory environment. Moreover, when comparing English in code-switched contexts with that of monolingual speakers, it is important to consider the inherent variations within English itself. Due to its diverse dialects and accents and a long history of linguistic contact, the definition of  ‘standard’ English is ambiguous. This suggests that the participants in our study may have exhibited different English accents from the outset, potentially influencing the results of our experiment.

Our study encountered a few limitations that affected the study’s results. Firstly, it is a vital variation given that our demographic was relatively small (16 people, with 14 college students), which may produce bias. Furthermore, all of them are self-reported bilinguals, even though with a linguistic background questionnaire, the clarification of “bilingual” remained unclear and contained various things. Our linguistic background questionnaire cannot showcase the diversity and dynamic of bilinguals panoramically and thus may ignore some related variations in code-switching. Secondly, though being collected and quantitatively analyzed, the data per se remained unclear in its accuracy in spontaneous code-switching in natural utterances. Taken together, this research contributes to the research looking into the relationship between code-switching and phonological convergence in Spanish-English bilinguals. The observed VOT lengthening during code-switching contexts suggests a dynamic interaction between languages where bilingual transfer does not have a bidirectional relationship. Bilingual speakers may also adjust their articulation based on the contextual demands of the linguistic environment. Future studies could further explore the implications of phonological transfer and its potential effects on language production in bilinguals.

Appendix I: Linguistic background questionnaire[1] [2] 

(1)  Is English your L1 or L2?

(2) Is Spanish your L1 or L2?

(3) Can you read and speak Spanish?

(4) Can you read and speak English?

(5) Do you speak any other language other than English and Spanish?

(if yes, which languages?)

(6) On a scale from 1-10, how often would you say you code-switch between English and Spanish? (Code-switching is the act of alternating between two or more languages or dialects within a conversation or phrase.)

(7) How positively or negatively do you feel about speaking Spanglish?

(8) Have you ever felt discouraged from speaking Spanglish?

  • yes
  • no

Appendix II: The Rainbow Passage in English and Spanish

When the kind sunlight strikes cold raindrops in the air, they act as a prism and form a rainbow. El arcoiris divide la luz blanca en muchos colores hermosos. Estos toman la forma de un arco tan largo, with its path high above and its two ends apparently beyond the horizon. There is, according to legend, a boiling pot of gold at one end. People look, pero nadie lo encuentra. Cuando un hombre busca algo más allá de su alcance, sus amigos pueden decir que está buscando la olla de oro al final del arcoíris. Throughout the centuries, people have explained the rainbow in various ways.

References:

Balukas, C., & Koops, C. (2015). Spanish-English bilingual voice onset time in spontaneous code-switching. International Journal of Bilingualism, 19(4), 423-443. https://doi.org/10.1177/1367006913516035

Banov, I. K. (2014, December 1). The production of voice onset time in voiceless stops by … BYU ScholarsArchive. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=5339&context=etd

Castañeda Vicente, M. L. (1986). El V.O.T de las oclusivas sordas y sonoras españolas. Estudios de fonética experimental, 2, 91-110.

Kasia Muldner, Leah Hoiting, Leyna Sanger, Lev Blumenfeld and Ida Toivonen.The phonetics of code-switched vowels, Carleton University, Canada https://journals.sagepub.com/doi/10.1177/1367006917709093

Lisker, L., & Abramson, A. S. (1964). A Cross-Language Study of Voicing in Initial Stops: Acoustical Measurements. WORD, 20(3), 384–422. https://doi.org/10.1080/00437956.1964.11659830

Ojeda, Adriana, Ana De Prada Pérez, and Ratree Wayland. Heritage Speakers and their Language Use: A Phonetic Approach to Code-Switching. University of Florida.

Olson, D. J. (2016). The role of code-switching and language context in bilingual phonetic transfer. Journal of the International Phonetic Association, 46(3), 263–285. https://www.jstor.org/stable/26352311

Piccinini, P., & Arvaniti, A. (2015). Voice onset time in Spanish–English spontaneous code-switching. Journal of Phonetics, 52(Sep), 121–137. https://doi.org/10.1016/j.wocn.2015.07.004 Voice onset time. (n.d.). ScienceDirect. Retrieved November 18, 2024, from https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/voice-onset-time

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Expressing Anger in Japanese and English Bilinguals

Kevin Kim, Shoichiro Kamata, Karin Yamaoka, Raine Torres, Max Fawzi

Japanese is often erroneously considered a “swearless language”, but anyone who has ever been yelled ‘しね’ (meaning ‘to die’) will confidently tell you that like all languages, Japanese has diverse ways of encoding abusive language. In Japanese ‘しね’ only becomes abusive language when in the context of being an insult, but in everyday situations the word simply means ‘to die’ without any connotation of insult. English differs from Japanese by having explicit profanities that carry a vulgar meaning independent of its usage context or syntactic environment. We conducted the following research to discover the discrepancy of semantic typology between Japanese and English profanities or abusive language, and if bilingual speakers endow varying emotional intensity to English profane lexica compared to Japanese abusive language. Our study shows that L1 Japanese L2 English bilinguals view English profanities as less offensive than their L1 English counterparts, report using these English profanities more frequently, and view the equivalent Japanese abusive language as more offensive.

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Introduction and Background

Languages differ significantly in how they encode and express emotions, particularly when it comes to the use of profanity as a means to express anger (for example in the context of an argument). This study examines profanities as a distinct subset of lexicon characterized by inherently vulgar or aggressive meanings, distinguishing them from other words or expressions that acquire such connotations only through context. In other words, in this paper, profanities refer to lexically explicit terms such as ‘fuck’ in English, that convey hostility or vulgarity without the necessity for context, and argue that Japanese lacks such a distinct subset, since words like  ‘しね’ (meaning ‘to die’) can convey aggression or intensity, but lack the explicit vulgarity found in English profanities. This study thus examines and defines profanities as vulgar lexica (found often in English) where its vulgarity is unaffected by its syntactic environment or context; distinguishing them from abusive expressions that only acquire offensive undertones within specific contexts (found often in Japanese). More specifically, Japanese speakers use “various markers of register rather than the explicit deployment of dysphemistic lexical items or expressions” (Jackson & Kennet 2021,1), where connotation of abuse is only endowed through syntactic and environmental inferences (context in which it is being used) even though there can be contextually impolite vocabulary derived from anatomical, excretory, and sexual sources like in English (Hoshino 1971, 31). We will refer to the vulgar and aggressive lexica of English as ‘profanities’ whereas ‘abusive language’ will be used for their Japanese counterpart lexica.

We argue that current studies on Japanese do not accurately reflect empirical use of abusive languages by native speakers. Medias (e.g. anime) that use more performative language tends to distort the perception of how Japanese speakers use language as media lexicons are often unreflective of native speakers’ lexicons. Through this study, we aim to focus on what native speakers consider to be consistently employed in their everyday language.

With our definition of profanities, it assumes a discrepancy of linguistic equivalence between English profanities and Japanese abusive language in its aggressiveness in its use. Therefore, it raises a question; How do Japanese L1 and English L2 speakers juggle the two discrepant lexical categories of ‘profanities’ and ‘abusive language’ and navigate through the lack of equivalence as a bilingual?

We aim to gain an understanding of the cognitive processes that occur for bilingual speakers, when conceptualizing constructs that are not lexically represented in their L1 and discrepancies in linguistic equivalence.

A research by Dewaele (2016) offers a valuable insight into self-reported perception of English swear words by L2 English speakers. The findings show that English LX users (non-native English speakers) over-estimate the offensiveness of most negative emotion-laden words, and avoid using most offensive emotion-laden words. On the other hand, a relevant study by Gawinkowska et al. (2013) found that bilingual speakers are more hesitant to use strong expletives in their L1 than in their L2, likely because they feel less bound by normative influences when speaking in their L2. As such, existing research has presented conflicting results, adding layers of complexity to bilingualism and emotional perception of abusive language in L2 languages.

We expect cultural aspects to play a role in the perception as well; Japanese cultural norms generally discourage direct expressions of intense emotion. One way this manifests is through face, as in outward appearances. Lin & Yamaguchi (2011) state that Japanese culture places greater importance on saving face, as face in collectivist cultures is concerned with an individual’s position in the social hierarchy rather than personal achievement like in individualistic cultures; there is also a tendency to avoid conflict and maintain interpersonal harmony in collectivist cultures. By directly expressing strong emotions, one would lose face in Japanese society and thus there is a social pressure against directly expressing intense emotion. Synthesizing the relevant studies and Japanese cultural aspect, we hypothesize that L1 Japanese speakers will perceive English profanities as being less emotionally charged than their L1 English counterparts. We can also expect L1 Japanese speakers to rate Japanese abusive language roughly the same as their English profanity counterparts or as less offensive overall.

Methods

2.1 Participants

The population of our study is L1 Japanese L2 English speakers, with our control group being L1 English speakers having no knowledge of Japanese. L1 Japanese L2 English bilingual participants are Japanese nationals who did not grow up speaking English at home; their English proficiency were established in the demographic section of the survey including questions regarding their language background. Furthermore, all participants are current college students for ease of recruitment and consistency, putting the age range between 18-28 years old, an age group which likely has the same general vocabulary and therefore slang/profanities, allowing for more homogenous data.

2.3 Design

The survey method was chosen to measure perceptions of both Japanese abusive language and English profanity. It consisted of two phases, where phase 1 focuses on the translation and interpretation of English profanities, and phase 2 focuses on the emotional charge and frequency of use of profanities.

2.3.1 Phase 1

Japanese media often, for performative effect, distorts how abusive language is used; this however does not reflect how native speakers use abusive language. We thus established a list of 10 Japanese abusive expressions with our own English translations, and asked a group of L1 Japanese L2 English speakers (N1 = 14, 7 male, 7 female) to translate the predetermined English words into Japanese. The results became a basis for the subsequent phase and also a tool to identify abusive lexica that native speakers (18~28) actually use.

2.3.2 Phase 2

A separate survey was sent to both our control group (N2 = 16, 8 male, 8 female) and to our experimental group (N3= 13, 3 male, 10 female). The survey asked participants to rate on a 5-point scale (1 = very low, 5 = very high) with regards to a given abusive expression/profanity (1) how well they understand the meaning, (2) how offensive/emotionally charged it is, and (3) how frequently they use it. The control group of L1 English speakers rated solely English profanities, while our experimental group rated both English profanities and Japanese abusive language.

2.4 Manipulation            

To standardize the implied usage context of the profanities (as emotional intensity could be influenced by the varying situations that participants imagine its usage to be), every survey were presented with a GIF of two men arguing, to standardize the perception that the profanities/abusive language in question are used by a person demonstrating anger. Moreover, phase 2 had two versions of the same survey, where Version 1 asked participants to rate English profanities first and of Japanese abusive language second, and vice versa. This was done in hopes of mitigating anchoring effects or priming effects that could bias our findings.

Figure 1: GIF presented to participants during phase 2 survey 

Results and Analysis

3.1 Phase 1 Results

This phase primarily served to establish the abusive language in Japanese that reflected the actual terms used by native speakers. A key finding was in regards to the perception of “shit” and “fuck”: L1 Japanese speakers tend to view “shit” and “fuck” as synonymous when translated into Japanese. Approximately 86% of respondents translated both “shit” and “fuck” as 「クソ」(kuso). This pattern likely reflects the absence of a direct Japanese equivalent for the word “fuck.” Instead, respondents opted for 「クソ」(kuso), which semantically corresponds more closely to “shit” as it denotes fecal matter. This semantic overlap highlights a gap in linguistic equivalence, influencing the way these terms are interpreted and used in the context of L1 Japanese speakers.   

Another key finding was that the translations for “dumbass” and “moron” were predominantly split between two responses: 「バカ」(baka) and 「あほ」(aho). Slightly more respondents translated “dumbass” as 「バカ」(baka), while “moron” was slightly more frequently translated as 「あほ」(aho). For the subsequent phase of the study, we selected the more commonly chosen translation for each term, though the differences were minimal. This suggests that, for Japanese speakers, profanities targeting intellectual levels exhibit limited variability in their translations, possibly reflecting a convergence in semantic interpretation.

The patterns presented were indicative of the nuanced ways in which abusive language is conceptualized and translated by L1 Japanese speakers. Specifically, the findings highlight the challenges of mapping English profanities to Japanese equivalents due to cultural and linguistic differences.

3.2 Phase 2 Results

Quantitative analysis of phase 2 reveals that on average L1 Japanese bilinguals view English profanities as 0.73 less offensive on the 5 point scale than L1 English speakers, with our experimental group rating the 10 English profanities as an average of 2.73, and the control group rating them as 3.45. The largest differences were found in “Ugly Bitch” (difference of 1.76) and the more commonly used “Fuck you” (difference of 1.42), which reflects a significantly different attitude towards even more common swearwords. Our experimental group also viewed the two most commonly used profanities “Shut Up” and “Fuck” as more offensive, with small differentials of 0.47 and 0.33 respectively. Our experimental group however, also rated the selected 9 Japanese translations at an average of 3.70 on the offensiveness scale (i.e. 0.25 higher than the English profanities), with the most offensive being 死ね, equivalent of “Fuck you” with a rating of 4.69 on the offensiveness scale.

Figure 2: Summary of the offensiveness of English profanities and equivalent Japanese abusive language

When it comes to frequency of usage, L1 Japanese bilinguals also reported using the English profanities at a higher frequency, with self-reported frequency being 0.87 points higher than their L1 English counterparts. This was the case for almost all English profanities across the board with the exceptions of “Fuck” and “Ugly Bitch” which had near equal usage; the largest differentials were found in “Moron” (difference of 1.48) and “Dumbass” (difference of 1.35). Interestingly, L1 Japanese speakers reported a rather low frequency of usage for the counterpart Japanese abusive language, with an average of 1.85 on the 5 point frequency scale. The most frequently used one being 「バカ」equivalent to “Dumbass” at 3.08, followed farther behind by 「クソ」 equivalent to “Fuck” at 2.38. This reflects the less frequent use of abusive language in Japanese compared to English which uses profanities more freely. This also corroborates the higher offensiveness of Japanese abusive language, which is used more infrequently and thus packs more of a punch.

Figure 3: Summary of the self-reported frequency of usage of English profanities and equivalent Japanese abusive language

Discussion and Conclusion

4.1 Phase 1 Discussion

In Phase 1, we found that L1 Japanese speakers used the same word 「くそ”」 (kuso) as an approximation for both “shit” and “fuck”. While this was not something that we had initially hypothesized, our findings in Phase 1 supported the idea that the Japanese language has less explicit profanities as previously found in research such as Jackson & Kennet (2021), highlighting the semantic overlap in the translation of “shit” and “fuck”, which underscores the limited availability of distinct Japanese terms that capture the unique connotations of these words in English. Similarly, the minimal variability in the translation of “dumbass” and “moron” suggests that Japanese speakers may perceive insults related to intellectual capability as largely interchangeable, pointing to a possible variability from L1 English speakers in how such terms are employed and understood.

4.2 Phase 2 Discussion

In Phase 2, we found that L1 Japanese speakers viewed English profanities as less offensive than L1 English speakers in all but two instances (“Shut Up” and “Fuck”). This aligned with our hypothesis that L1 Japanese speakers would perceive English profanities as being less emotionally charged. However, this contrasted with the findings of the Dewaele (2016) study which found that non-native English speakers would overestimate the offensiveness of English profanities and avoid using them. Our findings, instead, seemed to align more with Gawinkowska et. al (2013) which found that bilingual speakers were actually more inclined to use strong expletives in their L2 because they felt less bound by the norms of their L1. In our study, we saw evidence of this from the higher rates of usage for English profanities by L2 Japanese speakers than L1 English speakers. Japanese L1 speakers also rated the Japanese approximations of English swear words as being higher in offensiveness than the English swear words themselves. In the midst of conflicting research, we found that our findings followed similar patterns to Gawinkowska et. al. This may be due to the deeply ingrained collectivist cultural norms and emphasis on face-saving that exists in Japanese culture (Lin & Yamaguchi 2011) that may make L1 Japanese speakers more sensitive to abusive language in their native tongue.

4.3 Overall Discussion

This study offers some insight into the perceptions of emotional words in an L2. In our case, this refers to the use of profanities that are explicit without context for speakers who are familiar with abusive language that require context to be abusive. Research that helps understand these experiences will hopefully contribute to a wider understanding of interpersonal connection by identifying the ways language can cause miscommunications due to differences in culture as well as the language itself. Interestingly, additional observations suggest that non-English speakers often react with surprise or discomfort when exposed to the meaning of English profanities. In a street interview conducted by Asian Boss (LINK), Japanese people shared that they find such language uncomfortable and showed that abusive words are rarely used in Japanese culture. This observation also occurs among English speakers with Japanese people. According to the discussion in the Podcast “Hapa 英会話 Podcast – 第305回「汚い言葉遣い」”(LINK) , some English speakers try not to use the profanity with Japanese people even when they are talking each other in English. This similarity shows that hesitation from using profanity comes from the differences across cultural backgrounds regarding when it is appropriate to use profane language, which gives insight to the experiences of Second Language Learners as they navigate unfamiliar territories. These reactions further emphasize the cultural and linguistic differences in how profanities are perceived and used between English and Japanese speakers.

While our research was limited to only include college-aged students, future research would ideally expand the scope to include a variety of ages and educational backgrounds. Future research could also compare our findings with Japanese L1 speakers to another L1 language with contrasting conventions of abusive language.

References

Dewaele, J.-M. (2016). Thirty shades of offensiveness: L1 and LX English users’ understanding, perception and self-reported use of negative emotion-laden words. Journal of Pragmatics, 94, 112–127. https://doi.org/10.1016/j.pragma.2016.01.009 

Gawinkowska, M., Paradowski, M. B., & Bilewicz, M. (2013). Second language as an exemptor from sociocultural norms: Emotion related language choice revisited. PLOS ONE, 8(12), e81225. https://doi.org/10.1371/journal.pone.0081225

Hoshino,  Akira  (1971). Akutai  mokutai  kō  –  akutai  no  shosō  to  kinō. [Thoughts  on  Abusive  Language.  Aspects of Abusive Language and its Functions]. Kikan jinruigaku  2(3): 29– 52.

Jackson, L., & Kennett, B. (2021). Slang and taboo language: An analysis of swearing guides for L2 Japanese learners. Electronic Journal of Contemporary Japanese Studies, 21(2). Retrieved from https://japanesestudies.org.uk/ejcjs/vol21/iss2/jackson_kennett.html

Lin, C.-C., & Yamaguchi, S. (2011). Effects of face experience on emotions and self-esteem in Japanese culture. European Journal of Social Psychology, 41(4), 446–455. https://doi.org/10.1002/ejsp.817

Relevant Info: Hapa 英会話 Podcast. (2020).  第305回「汚い言葉遣い」[Podcast]. Retrieved from https://podcasts.apple.com/jp/podcast/hapa%E8%8B%B1%E4%BC%9A%E8%A9%B1-podcast/id814040014?i=1000491739815  Asian Boss. (2018). Japanese React to English Swear Words [YouTube video]. Retrieved from https://www.youtube.com/watch?v=KHpw5p8qCrI&t=61s

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Generational Speak: Investigating Sibling Language Dynamics in Spanish-Speaking Californian Families

Asher Erkin, Christine Kim, Valerie Morales, Karoline Vera, Camilla Zorzi

Why are younger siblings more likely to be excused for their lack of native language proficiency — and in turn, older siblings expected to be fluent? Following this common perception of bilingual speakers, our group hypothesized that in second-generation, Spanish-speaking households, older siblings would be less likely to produce speech errors and instances of code-switching than their younger siblings when instructed to describe scenes from a popular animated movie, Shrek. By asking sibling pairs to take our survey, transcribing their speech productions, and analyzing their differences in speech patterns in the context of sibling order and other demographic details, we showed that there was no obvious correlation between sibling order and fluency. However, based on self-reported personal experiences that participants believed had influenced their native language production, we observed that there are many more sociolinguistic factors that come into play when determining speakers’ comfort levels switching between their L1 and L2 languages.

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Introduction and Background

While living in Los Angeles, the city with the largest Spanish-speaking population, we wanted to make use of this opportunity to explore the speech patterns that reside in second-generation, Spanish-speaking homes. Research indicates that older siblings often introduce English to their younger counterparts due to earlier and distinct sociolinguistic experiences (Obregon, 2011). Compared to parents, siblings tend to be more open to acquiring English and are more prone to a phenomenon called code-switching prevalent among bilinguals. Schools and jobs they go to provide more opportunities for English exposure, which then promotes bilingualism. In our study, all participants from second-generation, Spanish-speaking families expressed that Spanish is the main language used at home, whereas English is commonly spoken in public places, increasing the likelihood of code-switching. Previous studies reveal that older siblings commonly learn Spanish first at home, then later on learn English through school and friends, which helps them build a stronger Spanish foundation than their siblings due to their earlier exposure. Given that there is strong evidence that multilingual older siblings are often responsible for exposing their younger siblings to English (Obregon, 2011), we hypothesize that older siblings will have a stronger connection to their native language and will produce a more standard Spanish speech than their younger siblings. In this study, we wanted to analyze how sibling interactions in bilingual families impact language development, with key implications for approaches to learning and linguistic support in multilingual communities.        

Methods

We recruited four groups of two or more bilingual siblings from second-generation, Spanish-speaking homes in Los Angeles, California. Each sibling filled out a survey with demographic background questions (age, primary language at home, gender, etc.) and an image-based storytelling exercise showing sequences from the film Shrek. They were given a collection of ten photographs and instructed to tell a story in Spanish. They were urged to record each narration separately so that the stories might be intricate and unique. 90 audio tracks, each lasting under 60 seconds, were generated as a result of this method.

Figure 1. Survey instructions.

Figure 2. A still from a Shrek sequence presented in the survey.

The recorded narratives were transcribed, and we examined the transcripts to look for instances of speech hesitations, code-switching, and self-corrections. Participants were found to be code-switching when they alternated between Spanish and English, and speech hesitations included grammatical, vocabulary, and pronunciation instances. To find linguistic trends in each sibling, we measured how frequently these instances occurred. To see how the language use of the older and younger siblings varied, we compared the results. We reasoned that older siblings would be more comfortable and proficient in Spanish, which would be demonstrated by fewer language switches and fewer errors. On the other hand, we expected the younger sibling to exhibit more frequent code-switching to English. Our goal in doing this type of study was to learn more about how multilingual siblings maintain their Spanish proficiency in a family setting and use their languages in diverse ways.

Results and Analysis

Analyzing the data and the recordings that we transcribed, we noted older siblings had descriptive language, using words and terms that not only described the scene but also described what the characters may be thinking or feeling based on the image. If the older siblings did not know how to describe some of the words, they would use circumlocution or find other ways to describe what gaps or errors they may have in their speech. For example, one of the older siblings described a rake as “que es una escoba, pero no es una escoba.” However, the attention to detail may have led to an issue among some of the recordings. Some of the participants showed a lot of hesitation, manifesting in fillers in their recordings. Some of the younger siblings showed more examples of code-switching and overall grammatical errors from the prescriptive grammar perspective. However, they were relatively strong and capable of showing a strong grasp of the language. However, there is no consistent language use among the older siblings and the younger siblings. The only similarity was the use of the filler words, where the siblings would say “uh” or “um,” which is the English use of the filler word, in comparison to the “eh” use of the Spanish filler word. This means that the siblings were most likely comfortable in English to rely on these filler words despite speaking in Spanish.

Overall, the results of the study were inconclusive. It is clear that there was no common pattern among the older siblings and the younger siblings as described in our hypothesis. In reality, there was a scattered level of grasp in Spanish. Some of the younger sibling participants were better at speaking Spanish in comparison to the older siblings, and there were also older siblings who were more fluent in comparison to the younger siblings. This may have been due to the research design and the way participants were recruited for the experiment. There were even some speakers who stated in the self-reporting that they felt more comfortable speaking Spanglish, a language variety that combines English and Spanish. For example, one participant stated: “…I do speak more English to my siblings, while I do try to speak Spanish, but I do struggle… I speak a mixture of ‘Spanglish’ if anything.” This indicates that the sudden switch to just Spanish may be a difficult switch to trigger. We can analyze Spanglish as “setting the foundations for forming one’s identity, while simultaneously maintaining their culture” (Kaprielian, et al), or as the idea of code-switching and the idea of a language that is characterized by its switch between English and Spanish. This language use has a negative connotation due to its lack of being one language or the other. However, this notion is inherently harmful as it instead shows a unique language identity.

Figure 3. A funny comic about Spanish-English code-switching and Spanglish.

One important point of information to target is the age of the participants, where the oldest participant is 32 years old and the youngest participant is 11 years old. This is an important angle to consider in regards to the analysis. Despite being from similar households, we cannot assume that the siblings emerged in similar language experiences. Thus, this presents a level of difficulty in grasping where each sibling resides in terms of language. This is a complex issue, and we cannot fully comprehend or gather what the upbringing was like for each child, as individual experience or time spent with parents may also demonstrate some understanding in the language differences. The age range of the younger children is another important factor, as the younger children may not be fully able to give a clear analysis given that this is something outside their age range, which is something that needs to be altered in further iterations of this study.

Spanish-speaking identity is an important factor to consider when understanding why there are different levels of fluency among the Spanish speakers. As Spanish is becoming an increasingly common language in California (US Census), people’s relationship with the language is changing. Individual experiences will impact how one approaches the language, as some may feel more comfortable speaking Spanish in public. The identity of being a bilingual speaker of Spanish and English is changing, where the younger generation or the younger siblings may feel pride and adapt their Spanish speaking identity as something they are proud of in comparison to the older sibling, who may have previously rejected this identity of themselves when Spanish was a less commonly spoken language in California. It is difficult to reverse the images and associations that may have been created for the older sibling but instead may be implemented for a younger sibling whose language is beginning to develop. Their understanding of their relationship to language is different in comparison to the older sibling. However, this cannot remain consistent among all siblings and speakers of Spanish, and this will vary greatly through individual experience.

Discussion and Conclusion

We chose to analyze speech errors and instances of code switching to represent the level of fluency of each sibling pair because we primarily wanted to gauge the difference of these productions between the younger and older siblings. We had expected to find that there would be a clear increase in these behaviors for the youngest sibling, though that was not the case — the level of comfort each participant pair had with their native languages seemed to be more reliant on their self-reported levels of exposure than their sibling order. Though our study mainly sought to correlate sibling order with L1 language fluency and thus did not focus as much on objectively analyzing personal experiences and exposures, we believe that relying upon the participants to self report these aspects of their lives gives us enough of an idea of the bigger picture to determine that this was indeed a greater influence on their L1 language production than solely sibling level.

Thus, we observed that for bilingual second generation Spanish speaking households, the level of comfort that a speaker has in switching between their L1 and L2 languages is impacted by many social and cultural experiences that cannot be analyzed with a simple sibling order heuristic. In the future, we would like to perform a more rigorous analysis of participants’ backgrounds — particularly during their early language development — by redesigning our experiment. Instead of requesting a description of 10 screencaps of a popular form of media, we would have asked them to describe a smaller number of their most vivid memories of L1 language usage and learning in early stages of development. While L1 fluency is undoubtedly impacted by individual life experiences that extend beyond this period, this method would allow us to specifically correlate the impact of formative linguistic experiences with their comfort switching between their L1 and L2 languages.

Ultimately, our project idea sought to address one aspect of the stigma within bilingual communities against members who are not fluent in their L1 languages. While older siblings may be expected to be more fluent in their native language than younger siblings due to social expectations or assumptions, we concluded that fluency cannot be solely attributed to this factor. We also encourage readers to be mindful of the fact that the concept of cross-linguistic fluency exists within the rigid and colonial boundaries of natural language. The sociolinguistic factors that affect this trait are more opaque than they may seem, and fluency is simply a matter of being able to quickly categorize linguistic features between L1 and L2 on demand. We hope that this reframing of fluency and natural language shows that perceived markers such as sibling order should not be used to cast judgment upon speakers.

References

Census.gov. (n.d.). U.S. Census Bureau quickfacts: Los Angeles County, California. https://www.census.gov/quickfacts/losangelescountycalifornia.

Kaprielian, L., Santana, O., & Sadiq, S. (2024, May 27). Languaged Life. http://languagedlife.ucla.edu/bilingualism/code-switching-a-phenomenon-among-bilinguals-and-its-deeper-role-in-identity-formation/.

Obregon, N. B. (2011). Older siblings teaching language skills and early literacy skills in their play with younger siblings / Nora Briselda Obregon. University of California, Los Angeles. https://www.proquest.com/dissertations-theses/older-siblings-teaching-language-skills-early/docview/879657630/se-2?accountid=14512.

Shin, S. J. (2002). Birth Order and the Language Experience of Bilingual Children. TESOL Quarterly, 36(1), 103–113. https://www.jstor.org/stable/3588366.

Tavits, M. & Pérez, E. O. (2019). Language influences mass opinion toward gender and LGBT equality. Proceedings of the National Academy of Sciences 116(34): 16781-16786. https://pubmed.ncbi.nlm.nih.gov/31383757/.

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Influencer Speech and Indexicality

Shogo Payne, Olivia Brown, Jade Reyes-Reid, Ricardo Muñoz, Priscella Yun

Stereotypically, people consider TikTok influencers to be vapid and unimportant. However, through our research on the language of TikTok influencers, we have found that through particular lexical choices, influencers establish their niche within the beauty industry by appealing to the emotions of viewers, becoming vessels for product promotion and marketability. Our work has proven that the greater frequency of inclusive and second-person pronouns, as well as language heavily using imagery and hyperbole, is the key to success for beauty influencers. We compare videos from five of TikTok’s most popular beauty influencers to see if our targeted lexical features can be shown to not only correlate with an increase in popularity on the platform but also to engage viewers as part of an exclusive community. Creators and brands will benefit from awareness of these linguistic tools’ ability to promote their message and products, while also giving them linguistic factors to consider in terms of marketing.

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Background

In recent years, TikTok has risen to unfathomable popularity, overtaking leading social media apps. While the premise of short-form content like that of TikTok is not new – its predecessor being Vine – TikTok is different in that it has the ability to reach mass audiences and create communities centered around a person and their interests. This in turn gets heavily exploited by brands eager to hand out sponsorships in an attempt to market to these communities of interest.

Many of the larger “niches,” a term we define as a subculture of TikTok, establish themselves as bona fide online communities through a distinct style of content made to satisfy viewers’ expectations from creators. While this “style” of content is often related to the niche of interest, creators’ identities undeniably play a role in the reception of such content. Afterall, two creators in the same general niche may attract individuals with different preferences as a result of the linguistic differentiation. Thus, the language used by Tiktok creators is equally important in establishing a style which connects with audience members.

In the world we live in, we cannot escape from media information. Constantly, we endure such things as advertisements, billboards, and TikTok notifications. The amount of words and numbers we take in every day seems to be increasing, almost violently so. Think about how Instagram creators refer to their content output as their “feed,” which we interpret literally: a stream of consciousness which their followers consume. Consequently, and subconsciously, we have to be able to “filter” what knowledge we take in, that knowledge which is concerning to us. TikTok and similar social media platforms already have a system in place to expedite this. TikTok’s “For You” page, the home page, is where the app’s analytical system gathers recommended content, based on the user’s recent viewed-content activity, to show the user. Psychologically, this is what we deem as “influencer speech.” This phenomenon of speech has been noted by many including new articles, like in one by VICE, stating that it is “the perfect balance between buoyant yet flat; it gives just enough away, without really giving anything away; it keeps me from scrolling past the video” (Hall). The visual and audio content of a video needs to be attention-grabbing in a novel way to the user, in order to not be scrolled away. If the TikTok creator cannot capture the attention of the user within the first couple of sentences, it may as well be an admission of defeat. If we look at it differently, the main property that influencer speech holds is the ability to build an image or identity in your mind that psychologically indexes for a particular niche which may or may not suit us.

The duty of a TikTok influencer is to relate to audiences while also being marketable to brands for the purpose of product promotion. With the importance of strategic language in mind, we ask the question: Do TikTokers modify their speech to increase marketability? Our expected answer to this question was yes. Through observation of a collection of lexical features that we deem influencer speech, we found correlations with greater frequency of positive feedback, as well as indexation of leadership within a specific online community.

Previous investigation into social media advertising has proven social media promotion to now be more effective than traditional TV commercials (Chen, et al. 2023). This finding motivated our research in proving the importance of understanding social media advertising in this social media-driven landscape we find ourselves in. Additionally, a study conducted by Munaro et al. suggests that certain lexical items can increase audience engagement and brand partnerships (Munaro, et al. 2024). Previous research has also indicated that lexical terms act as facets of one’s identity in discourse (C.M Davis. 2020). We wanted to take this research a step further to address how particular lexical features often associated with influencer speech may help or hinder one’s marketability within the volatile landscape of TikTok influencing. It was important for us to address this question in a way that would be easy for non-linguists to understand while providing flexibility, so that any conclusions we found should not be so prescriptive as to limit the individuality inherent in casual speech.

We decided to look at the beauty community within TikTok for our data collection not only for its large scale – 1⁄3 of American adults use TikTok, with the majority of those users being women between the ages of 18-24, meaning the majority of TikTok users are likely beauty consumers (Bestataver 2024) – but because product promotion within this niche is highly prevalent and interwoven with the content. The content, as we will be focusing on it, will be the aforementioned lexical terms.

There is a common misconception and stereotype that influencer speech, particularly within the beauty community, is vapid and meaningless. However, we reject this ideology, instead asserting that beauty influencers use particular lexical features to garner engagement and increase marketability. We call this bundle of features “influencer speech”, or “I.S.” in its abbreviated form.

The features we used to define influencer speech are as follows: precision in synonyms, pronoun usage, and hyperbole. Firstly, precision is the usage of descriptive, repetitive synonyms used to build imagery for audiences that creates a psychological closeness to the product. Secondly, we examined usage of particular types of pronouns such as first-person, second-person, and inclusive pronouns (as in we and let’s) to gauge how influencers engaged with their audiences through their speech. Previous research asserts that inclusive language allows influencers to connect with and gain reputability amongst their audience (Prudencio, et al., 2023), thus inspiring us to look more closely at TikTok beauty influencers’ use of inclusive pronouns. Furthermore, in a podcast about effective persuasion, Professor Jonah Berger describes how tapping into consumer identities causes them to call to action while feeling a closeness (Jonah, 2023). Lastly, we looked at hyperbole, which we consider any speech that exaggerates a product’s quality and novelty and/or a consumer’s need for the product. We included hyperbole since research on its use within everyday speech suggests its use as ‘highly’ interactive, which emphasizes its potential power as a lexical term to connect with audiences (McCarthy & Carter, 2004). Within this category of hyperbole, we looked at phrases such as “life-changing,” “you need this product,” or influencers describing products as “the best ever.”

Methods
Previous research indicates TikTok’s immense value as a tool to gather legitimate sociolinguistic data (Alajmi, 2023). We examined the speech of five top TikTok beauty influencers by first inspecting five non-sponsored videos from each respective creator to create a baseline idea of their speech when they are not advertising a product. We then compared this data against their speech when they were advertising a product or doing a review, surveying five additional videos of this kind and recording how many of our target lexical features were used and how often. The relative frequency of each lexical item was counted in terms of categorizing every video into whether it contains more hyperbolic language, precision, or pronoun usage. This in turn would allow us to gauge a shift in influencer speech when promoting products through analysis of frequencies. Ultimately, this would allow us to determine the potential most effective aspects of influencer voice when it comes to influencing audiences.

We knew it was vital to consider the context of content creators’ backgrounds, which may lead to inherently unfair comparisons. This is why the five influencers we chose are leading American makeup creators known to innovate in products and methods of application. All five have at one point or another been looked to for advice and to dictate what the next trending item or application method would be. As all of the creators are American, we can generally consider their cultural backgrounds to be similar, therefore eliminating concern surrounding cultural differences as a factor in their speech.

On each video, we documented the number of views and likes garnered, then took a sample pool of 20 comments to evaluate whether the responses were mainly positive, negative, or neutral. Our evaluation process was this: comments expressing approval, excitement, or support for either the product, video, or creator are positive; comments unrelated to the topic or creator are neutral; comments expressing disapproval, disappointment, or disagreement with the video or creator are negative. We then compared these findings for each of the TikTokers to see what lexical features or variables are associated with influencers and how their presence affects the audience.

Results

Overall, we found that influencers generally increased their usage of second-person pronouns and synonyms across all promotional content. We also found an increase in use of inclusive pronouns, with the exception of one creator from our sample, Meredith Beauty. As for first-person pronouns and hyperbolic language, we had more inconclusive results, as usage did not shift much from promotional to non-promotional content within our sample. As seen in Figure 1.1 below, inclusive pronoun usage increased 106% in sponsored content, second-person pronouns increased 62%, and synonyms increased 141%, while first-person pronoun usage decreased slightly by 18%, and hyperbole similarly had a slight decrease by 14%.

Figure 1.1. Average lexical features used in promotional videos versus non-promotional videos.

We also observed a higher number of positive comments, views, and likes within sponsored videos. Inversely, neutral and negative comments seemed to decrease with sponsored content. Figures 1.2 and 1.3 showcase our data on the quality of comments and the levels of engagement. Positive comments were shown to increase slightly by 1% in sponsored content, indicating inconclusive results due to the miniscule amount of change from sponsored to non-sponsored content. Neutral comments decreased by 16%, and negative comments decreased by 10%. As these numbers are relatively small, we cannot draw any complete conclusions from this sample. However, a large uptick in viewership of content was noted in our data, with a 106% increase for sponsored content. Additionally, likes increased by 125% in the sponsored content we observed.

Figure 1.2. Average comments for promotional versus non-promotional videos.

Figure 1.3. Average engagement across promotional versus non-promotional content.

Overall, we found that our identified lexical features of influencer speech were used more often in promotional content, indicating a correlation between usage of influencer speech and product promotion.

Discussion and Conclusion

Our findings on influencer speech and promotional content on Tiktok carry various implications in real world application of marketing strategy and engagement. For instance, our findings suggest that certain lexical terms, when used strategically in social media content, can result in higher levels of engagement. We hypothesize that this higher engagement results from creators’ indexation of a leadership role in the beauty community through the use of lexical terms audiences connect to, aiding in the development of trust between creator and consumer. Our results also raise questions about the role of influencers in our society. Rather than just provide entertainment, there is immense value in their role as a talking head for product promotion. Our analysis could help us demystify the distinction between entertainer and advertiser. Future research could examine influencer speech outside of the beauty community to see if these findings are consistent across all online influencing communities and platforms, rather than the TikTok beauty community alone.

Results that strayed from the overall trend of the data could correlate to numerous hypotheses. Demonstrating credibility by restraining from fallacies such as hyperboles and increased use of inclusive pronouns causes viewers to believe the review of the product is credible and therefore, increases the marketability of content. There may also be differences between personal speaking styles and brand guidelines that are required when creating sponsored content, such as promises to include certain phrases or even scripts given to influencers.

We acknowledge that limitations pertaining to scope occurred throughout our research project. Due to our project’s scale, we viewed 5 different influencers with 10 videos each. All the influencers were from similar backgrounds as rich, successful, American influencers. If we had more time, we could expand our sample size to include influencers from more diverse backgrounds to see if influencer speech is still used in other cultures. This revision could determine if the trends we found are generalizable. Additionally, influencers on TikTok are able to moderate their comment section, meaning our data gathered from comment sections could be inaccurate and cherry-picked by the influencer. Finally, we did not take video length into account. However, if we had more time, analyzing video length alongside these other features could reveal patterns relating to how often features were used per second or per minute, giving an even more accurate analysis of the data.

Despite these limitations, our exploration of influencer speech has revealed intriguing insights into how code-switching within influencer speech appears to aid marketability. Our thesis predicted that influencers used influencer speech more often in promotional content in order to increase marketability. After analyzing our data, we can say that this is partially true. Inclusive pronoun, second-person pronoun, and synonym usage did increase in promotional content, though our analysis of first-person pronouns and hyperbole was inconclusive. We hope that our research can serve as a catalyst for deeper inquiry into how persuasion appears in the digital world as a sociolinguistic tool.

References

Alajmi, N. M. (2023, August 1). The Speech of Social Media Influencers in Najd: Introducing a New Source of Sociolinguistic Data. Academy Publication. https://tpls.academypublication.com/index.php/tpls/article/view/6552.

Berger, J [Social Media Examiner] (2023, March 16). The Language of Persuasion: Magic Words to Get Your Way. YouTube. https://www.youtube.com/watch?v=6teWZLgvUso.

Bestvater, Samuel. (2024, February 22). How U.S. Adults Use TikTok. Pew Research Center. https://www.pewresearch.org/internet/2024/02/22/how-u-s-adults-use-tiktok/.

Chen, G., Li, Y., & Sun, Y. (2023, February 15). How youtubers make popular marketing videos? speech…Sage Journals. https://journals.sagepub.com/doi/full/10.1177/21582440231152227.

Hall, Alice. VICE. (2023, March 29). Why does everyone on TikTok use the same weird voice?. https://www.vice.com/en/article/k7zq49/why-everyone-uses-tiktok-voice.

McCarthy, Michael & Carter, Ronald. (2004). “There’s millions of them”: Hyperbole in everyday conversation. Journal of Pragmatics – J PRAGMATICS. 36. 149-184. 10.1016/S0378-2166(03)00116-4.

Munaro, A. (2024, July). Does your style engage? linguistic styles of influencers and digital consumer engagement on YouTube. ScienceDirect. https://www.sciencedirect.com/science/article/abs/pii/S0747563224000852.

Prudencio, A. B., Sherwin, C. C., Barcelona, J. A., Niduaza, B., & Tongawan, P. F. C. (2023, July). Stylistic and discourse analysis of the language of social … IRE Journals. https://www.irejournals.com/formatedpaper/1704877.pdf.

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Political Polarization: Why are you fighting in the comment section?

Kathryn Cunningham, Anna Tobey, Leia Broughton, Maya Athwal, Nicole Pacheco

Note: This article was written in Spring 2024, prior to Biden stepping down from the presidential race and Trump winning the 2024 presidential election.

Are all news headlines made equal? For our project, we analyzed the potential effects of framing in online news headlines on readership responses in the comments. Digital tools for political discourse are becoming increasingly popular, and we want to investigate how framing in the media can influence political cognition and amplify the political polarization we see in comment sections today. We hypothesized that different framings in headlines would provoke politically biased emotional responses against the opposing political party. We conducted critical discourse analysis of six different headlines pertaining to a singular political event — Michael Cohen’s testimony against Donald Trump — on two news sites from each of the following categories: left-leaning, right-leaning, and neutral. We then compared these analyses of the lexical and syntactic choices used to frame Cohen and Trump with the corresponding comments on each article. We observed high-frequency keywords and identified eight categories for different comment types, considering how each headline could have prompted the intense responses we saw. The results of this project are important in understanding the power of party framing and how it can divide us simply through subtle choices in language.

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Introduction

Have you recently read a comment section that looks more like a war zone and wondered: how did we get here? In our research project, we analyzed news headlines and comments trying to find the source, and we may have part of the answer. Digital tools for political discourse are becoming increasingly popular, and we wanted to better understand how framing influences political cognition and produces the political polarization we see in comment sections today. With this goal in mind, our project explores how framing in news headlines influences reader responses in the comments. Issue framing is when an author uses certain language to subtly present their opinion on a topic, and this can appear in anything from word choice to using passive voice to minimize someone’s culpability in an event. A single event or person can be presented in many different ways, and each of those ways could influence the reader into having a different opinion on the same event (Wang 2024). We specifically focus on party framing, which is when a frame is endorsed by a particular political party; this is extremely influential in the public’s formation of opinions — even more so than regular framing techniques. People will even dismiss a certain opinion just because it comes from the opposing party (Slothuus and de Vreese 2010). We hypothesize that framing in headlines can provoke emotionally-charged comments, with more negative and extreme headlines resulting in more hostility towards members of the opposing party.

Methods

We first analyzed six headlines from news sites of varying political affiliations, focusing on articles about Michael Cohen’s testimony in Donald Trump’s trial. As a control group, we first looked at headlines from PBS NewsHour and The Associated Press, which are perceived as more neutral news sources (Knight Foundation, 2018). Our two left-leaning news sites were The New York Times and HuffPost, and our right-leaning sites were Fox News and the New York Post (AllSides Technologies, 2024). To analyze these headlines, we looked into their uses of framing in their word choice and sentence structure and how these were used to assign blame and express the sites’ own opinions on Trump and Cohen.

After analyzing the headlines, we turned to the comment sections from the left- and right-leaning sources. The neutral sources did not have attached comment sections, and we felt that they served us best remaining as the control from which to compare our other headlines. In analyzing the comment sections, our goal was to see if there was a connection between negativity and framing in the headlines and patterns of hostility and rudeness in the comments. This method limited our options, with many potential news sources pay walling their comment sections or simply not including them at all. Despite the fact that most comments are made on social media (Stroud et al. 2016), we preferred to avoid social media comments, as we felt that they would likely be less genuine and more filled with trolls and “bots.” In order to best organize our analysis, we compiled the most popular comments from each source, and then we compared them to each other to find shared patterns. We built a categorization system, shown in Fig. 11, that best captures the nuance of each comment section in comparison to the others so as to make for better comparison and more accurate connections to the headlines.

Results and Analysis

Our results from our initial analysis of each news headline showed variations in the framing of characters, actions, and descriptions involved in the news story, dependent on each news site’s lexical and syntactic choices. We observed that, despite these variations, each news site’s framing generally reflected their established political bias. For example, the syntactic choices in framing Cohen’s character varies greatly between Fig. 6, which refers to Cohen as an “ex-con”, and Fig.1, which refers to Cohen by name. These choices aligned with the political bias of each news site, thereby demonstrating a consistent correlation between the linguistic framing of each headline and political bias of each site. AP’s headline was a bit more left-leaning than expected, but it was later reposted on HuffPost, proving their left-leaning bias.

Figure 1. Annotated headline from The New York Times (Left).

The New York Times does not mention Trump by name, but it reminds readers of the power Trump once possessed as president by mentioning the Oval Office. The “hush” of “hush money” creates a negative moral judgment against Trump, but overall, this is one of the more neutral headlines.

Figure 2. Annotated headline from HuffPost (Left).

HuffPost frames Trump as an object of ridicule in this headline, granting Cohen power over him. Interestingly, it focuses on a more “gossip” style of reporting rather than things relevant to the trial. The focus on berating Trump makes this headline very biased.

Figure 3. Annotated headline from The Associated Press (Neutral).

The Associated Press features a vaguely left-leaning headline. Cohen is granted credibility with connotations of celebrity, intrigue, and duplicity. There is a clear negative morality judgment against Trump in calling it a “scheme” instead of a “trial.”

Figure 4. Annotated headline from PBS NewsHour (Netural).

This PBS NewsHour headline is the most neutral of the six. They use an actual quote from Cohen, focusing on the facts.

Figure 5. Annotated headline from Fox News (Right).

The Fox News headline frames Cohen as bumbling and spiteful. Trump becomes a victim of a hateful Cohen in this frame, creating sympathy for Trump and a distrust in Cohen.

Figure 6. Annotated headline from the New York Post (Right).

The New York Post frames Cohen as untrustworthy by describing him as an “ex-con.” Trump is a clear victim in this version of events. The headline also implies that Cohen is dredging up “old” events to ruin Trump’s 2024 campaign.

Following this, we observed the top comments received by each article with a particular focus on keywords responding to the framing effects of the headline. Firstly, we observed a larger frequency of comments about Trump, the trial, and the general political situation, rather than of Cohen and his testimony. As predicted in our hypothesis, the more polarized headlines had more drastic and emotion-filled comments than the more neutral headlines. Both political sides were firm in their stance, unwilling to budge and change their perspective, with comments typically made to degrade or vilify the other side.

Using keywords and notes from our initial observations, we identified eight key categories of comment-types which reflected similar biases that we observed from our headline analysis (Fig. 11). We created a color-coding system for analyzing our top comments according to these categories to measure the frequency of each category within each news sites’ comment section.

Figure 11. Eight categories used for comment analysis.

As we hypothesized, hostile discourse, sarcasm and animosity, and insult or threat against the opposing party were consistently apparent across all four sources. However, we observed variations between left- and right-leaning discourse styles between both comment sections, and these are potentially related to the framing of each corresponding headline. These two comment analyses below demonstrate this difference in discourse style: 

Figure 12. Comment under article from The New York Times (Left).

 

Figure 13. Comment under article from the New York Post (Right).

We believe that these differences are potentially related to each party’s political and moral ideologies, which were reinforced by each headline’s framing. For example, higher frequencies of deflection and victim mentality among right-leaning comments might reflect defensive language in response to Trump’s victimization in right-leaning headlines and Trump’s vilification in left-leaning headlines.

As shown in Figs. 7 and 8, we observed that hostile discourse, insult or threat, and sarcasm or animosity had the highest measure of frequency in our left-leaning sources. Figs. 9 and 10 show that hostile discourse, victim mentality, rationalization, and insult or threat had the highest measure of frequency in both our right-leaning sources. Interestingly, we also observed that supporting discourse was present in both sides, particularly in responding to others’ comments to reinforce their political beliefs. We believe that these findings show potential consequences for politically biased news headline framing that are manifested in comment sections by the reinforcement of certain political ideologies and antagonization of opposing parties, creating a sort of “echo chamber.”

Figure 7. Comment categorization for The New York Times article (Left).

The New York Times comments tend to focus on the insinuation of Republican corruption. The comments were mainly directed towards Trump, attacking and vilifying him. When Cohen was mentioned, it was typically a positive association or connotation. Comments appeared heavily moderated, or perhaps the more neutral headline resulted in less intense comments.

Figure 8. Comment categorization for the Huffpost article (Left).

The HuffPost had less serious comments heavily filled with sarcasm, mockery, and insults towards Trump. With almost no mention of Cohen, the comments were mainly full of mocking and taunting remarks, with few attempted claims of substance.

Figure 9. Comment categorization for the New York Post article (Right).

The New York Post focuses mainly on the content of the article, with strong remarks that the trial was set up by immoral Democrats. With the victimization and support of Trump, Cohen is framed as a devious liar who cannot be trusted.

Figure 10. Comment categorization for the Fox News article (Right).

The Fox News comments had a mixture of the victimization of Trump and framing Cohen as an incompetent liar. The commenters also had a strong belief that the trial was fraudulent and biased.

Discussion and Conclusions

Our findings suggest that political framing in headlines through lexical and syntactic choices does create biased responses across the political spectrum. With political polarization in media becoming increasingly prevalent, especially considering 2024 is an election year, our findings are very relevant to discussions around the impact of media on public opinion and discourse. For instance, we found that headlines considered to be more neutral, such as the New York Times, resulted in less discourse between political parties, specifically with less engagement from the right, and the more biased headlines resulted in more hostile rhetoric and discourse in the comment sections between members of opposing parties. Therefore, our findings suggest that headlines that are considered to be more biased provoke stronger, more polarized discourse. Given that our study was limited by factors such as comment moderation and paywalls, a more comprehensive study might include social media responses or a broader range of politically-affiliated news sites rather than just the six we analyzed. For future research, we believe that our ideas can be expanded into a larger study using emerging AI models to analyze larger datasets from social media, which would yield more conclusive results. Perhaps they could detect bots and trolls on social media as well, removing that from consideration.

The next time you are scrolling through the comment section on a political piece, take a moment to recognize what might cause strong feelings one way or another and how that is really affecting your perception of current events. With the tools presented, you now might be able to understand why there is so much fighting in the comment section.

References

AllSides Technologies. (2024). AllSides Media Bias Chart. AllSides. https://www.allsides.com/media-bias/media-bias-chart.

Baratta, A. M. (2008). Revealing stance through passive voice. Journal of Pragmatics, 41(7), 1406-1421. https://doi.org/10.1016/j.pragma.2008.09.010.

Boydstun, A. E., Gross, J. H., Resnik, P., & Smith, N. A. (2013). Identifying Media Frames and Frame Dynamics Within and Across Policy Issues. New Directions in Analyzing Text as Data, 27-28. https://faculty.washington.edu/jwilker/559/frames-2013.pdf.

Gligorić, K., Lifchits, G., West, R., & Anderson, A. (2021). Linguistic effects on news headline success: Evidence from thousands of online field experiments (Registered Report Protocol). PLOS ONE, 16(9). https://doi.org/10.1371/journal.pone.0257091.

Knight Foundation. (2018). Perceived accuracy and bias in the news media. Gallup. https://knightfoundation.org/wp-content/uploads/2020/03/KnightFoundation_AccuracyandBias_Report_FINAL.pdf.

Slothuus, R., & de Vreese, C. H. (2010). Political Parties, Motivated Reasoning, and Issue Framing Effects. The Journal of Politics, 72(3), 630–645. https://doi.org/10.1017/s002238161000006x.

Stroud, N. J., Van Duyn, E., & Peacock, C. (2016). Engaging News Project: News Commenters and News Comment Readers. Center for Media Engagement, Moody College of Communication, University of Texas at Austin. https://mediaengagement.org/wp-content/uploads/2016/03/ENP-News-Commenters-and-Comment-Readers1.pdf.

Wang, H. (2024). Linguistic Analysis of News Title Strategies in Media Frame—A Case Study of ‘The Mueller Investigation’ in the News Titles of The New York Times and Fox News. Journalism and Media, 5(1), 342-358. https://doi.org/10.3390/journalmedia5010023.

Zhou, Z. (2022). Discourse Analysis: Media Bias and Linguistic Patterns on News Reports. Advances in Social Science, Education and Humanities, 637, 271-277. http://dx.doi.org/10.2991/assehr.k.220131.049.

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Dialogues of Fame: Unveiling Gender Dynamics in Celebrity Interviews

Elizabeth Escamilla, Penelope Hernandez, Kenzie MacDougal, Jason Ye

Human interaction is complex and, at a sociolinguistic level, can be challenging to parse. With that in mind, we chose to analyze celebrity interviews — definite and structured slices of conversation whose participants were conscious of the invisible future viewer. Informed and inspired by studies such as Julia T. Wood’s “Gendered Media: The Influence of Media on View of Gender,” Rossi and Stiver’s “Category-Sensitive Actions in Interaction,” and Tavitz and Perez’s “Language influences mass opinion toward gender and LGBT equality,” we investigate patterns of interaction and indexical shifts as they may be affected by the genders of the involved parties. Taking two-minute segments from each interview, we classified questions as personal or professional and invasive or appropriate. Anything deviating from expected interview etiquette was noted, whether that be word choice or tone of voice, as well as the reactions of any third parties. Most importantly, we classified the ways in which interviewees responded to invasive lines of questioning, specifically as one of the following: retaliatory questioning, a passive aggressive remark, a humorous deflection, a partial answer, or a direct answer. A significant trend of women receiving more invasive and personal questions quickly appeared, though our investigation suffers from a possible selection bias. Therefore, future investigations should pull from a much larger and more varied sample of interviews.

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Introduction and Background

Celebrity interviews aren’t conversations that take place in a vacuum; they may be viewed by hundreds, if not thousands, of people. Additionally, the predefined question-answer format of an interview makes it easier to parse for sociolinguistic analysis. Needless to say, we found celebrity interviews to be generous data points for analyzing patterns informed by the gender identities of the involved parties.

Studies like Julia T. Wood’s “Gendered Media: The Influence of Media on View of Gender” show us how the media’s representation of men, women, and queer people may affect a viewer’s understanding of gender roles. Problematic patterns are uncovered: “men and women are portrayed in stereotypical ways that reflect and sustain socially endorsed views of gender… depictions of relationships between men and women emphasize traditional roles and normalize violence against women” (Wood, 2013). Unlike fictional movies and television shows, the interactions recorded in celebrity interviews involve real people, or at least believable personas designed with the public eye in mind. It follows that interviews with respected, famous individuals play a greater role in influencing what people deem socially acceptable behavior. Thus, when audiences watch mistreatment of women play out with little to no consequence, they may feel validated in their own experiences with misogyny, as either a perpetrator or victim.

Media is both what its creator produces and what the viewer brings to their experience with it. The manners in which interviewers and interviewees carry themselves both reflects and defines current standards for human sociolinguistic communication. Inspired by “Category-Sensitive Actions in Interaction,” we hope to identify patterns in lines of questioning and the manner in which these questions are handled. That study outlines how boundaries of social membership are exposed in ordinary interactions — “the distribution of rights and constraints to perform certain actions creates boundaries in people’s activity space, which are typically respected but sometimes exposed or even crossed” (Rossi and Stivers, 2020). As it pertains to our investigation, when an interviewee is asked an invasive question, this may be classified as a transgression of these silent boundaries.

So, we aim to contribute to a growing body of work suggesting that different behaviors and patterns of interaction vary based on the gender of the interviewee, unfortunately often at the expense of women and queer individuals.

Methodology

We chose to study a variety of variables for this project, including the frequency of personal versus professional questions, word choice and tone of voice used by the interviewer, and the methods interviewees used to navigate controversial questioning.

Upon examining an interview, we followed a set of steps to extract and prepare the data for analysis moving forward. First, it’s important to classify any questions as being professional, personal, appropriate, or invasive.  Professional questions relate strictly to the interviewee’s work, while personal questions deviate from this. Similarly, appropriate questions are given to those that are deemed socially acceptable, such as topics commonly discussed with acquaintances, while invasive questions are not. Next, we take note of any speech or tone used by either interviewer or interviewee that may deviate from the expected etiquette of interviews. From here, we classify methods used by interviewees to ease out of or address uncomfortable questioning. We chose to classify these among the following: direct answer, partial answer, humorous deflection, passive aggressive remark, or retaliatory questioning. Humorous deflection involves the use of humor in an effort to avoid responding to the question. A passive aggressive remark includes any form of snarky or sarcastic response, including those done purposefully to attack the interviewer. Retaliatory questioning is the act of answering the original question with a question of one’s own. Finally, if the selected interview happens to involve more than one interviewee, it is important to also take note of any third party reactions or interactions to awkward questioning. 

To demonstrate our methodology, we will examine an interview with Scarlett Johansson and Jeremy Renner for their film The Avengers (2012). The first question, directed at Johansson, was: “Were you able to wear undergarments [with your costume]?” This question was labeled personal and invasive. Johansson responded with a passive aggressive remark and retaliatory questioning: “I’ll leave it up to your imagination, okay, whatever you feel like I should be wearing or not wearing under that costume” (Passive Aggressive Remark) and “What is going on? What? Since when did people start asking each other about- in interviews about their underwear?” (Retaliatory Questioning). Later on in the interview, Jeremy Renner is asked a question about an injury: “I understand you got hurt pretty badly though. How’d you do that?” This was labeled as professional and appropriate, and no other notes were taken as there was no unique use of tone, word choice, or navigation methods.

Results & Analysis

In this section, we will break down the details of our results and perform analysis on each individual dataset table (interviews); let’s start with some visuals demonstrating the overall statistics.

Table 1. This table shows the totaled data from individual datasets (interviews) into one table.

 

Figure 1. This graph shows the number of personal vs. professional questions the interviewees received based on their respective gender.

 

Figure 2. This graph shows the number of appropriate vs. invasive questions the interviewees received based on their respective gender.

Just from these few charts, we can already gauge a sense of skewedness, one that seems to confirm our hypothesis: female interviewees, regardless of the gender of the interviewer, are likely to encounter more personal questions compared to male interviewees. Indeed, we can see that 61% of the questions asked to female interviewees were personal, as opposed to 41% of the questions posed to their male counterparts (49% increase). On top of that, we found 39% of the questions asked to female interviewees were also invasive in nature, while only 17% were invasive for male interviewees, which is a 129% increase, more than twice as many invasive questions. This disparity in question types based on the interviewees’ gender is alarming.

To navigate these invasive lines of questioning, we found that male and female celebrities tend to employ different methods. Female celebrities mostly used retaliatory questioning, humorous deflection, and direct answers — the first two methods being more indirect ways of signaling to the interviewer that the line of questioning was inappropriate. Male celebrities, on the other hand, mostly used direct answers and passive-aggressive remarks, which we speculate is due to men feeling more comfortable asserting themselves in these socially invasive situations.

Now, having discussed the key points of our results, we will provide additional analysis on each individual dataset (interview) separately.

Table 2. Data for The Avengers interview with Scarlet Johansson and Jeremy Renner (Male Interviewer).

This first dataset/interview was already touched on in the previous section on methodology, it suggested the same disparity in question types between the female and male interviewees. Scarlet Johansson received a disproportionate amount of personal and invasive questions and had to defend herself using mainly retaliatory questioning, while Jeremy Renner received only appropriate or professional questions.

Table 3. Data for Dan Stevens and Emma Watson interview for Beauty and the Beast (Female Interviewer).

This dataset/interview is an outlier amongst all the other datasets. First thing we noticed is the empty “Methods Used to Navigate” column; we didn’t need to fill in any. All the questions were appropriate and professional with only one personal (but appropriate still) question directed at Emma Watson. Interestingly, this is also the only interview in our entire dataset pool with a female interviewer; more evidence and data would be needed to come to any meaningful conclusions about whether the gender of the interviewer correlated with the fact there were no invasive questions.

Table 4. Data for interview with Zendaya, Mike Faist, and Josh O’Connor for Challengers (Male Interviewer).

There are two invasive questions, and both were directed at Zendaya. The note-worthy takeaway here is the fact that both her co-stars Josh and Mike came to her support/rescue with direct answers trying to further alleviate the awkward situation after Zendaya responded initially with a retaliatory question.

Table 5. Data for interview with the cast of Star Wars: The Last Jedi (Male Interviewer).

Out of the three invasive questions in this dataset/interview, two were directed at a male interviewee (certainly an outlier too in and of itself). Here, we see the use of a passive aggressive remark employed by the male celebrity and a partial answer instead of a more direct one, though the tone does not detract too much from a direct one. The female interviewee employed a humorous direct answer; though a direct answer, the tone is more of just a humorous answer without the impact of a completely direct response.

Table 6. Data for interview with Christian Bale and Anne Hathaway for The Dark Knight Rises (Male Interviewer).

Both invasive questions were directed at Anne Hathaway, and humor and deflection were used to navigate the situation. All four of the questions directed at her were personal. While the male interviewee also received only personal questions, none of them were invasive.

Circling back to our hypothesis one more time after the more detailed look into each dataset, we can establish the clear gender bias in type and appropriateness of questions posed to celebrities in interviews, with female celebrities disproportionately subjected to more personal and invasive questions — confirming our suspicions and reflecting societal attitudes and expectations around gender.

Discussion and Conclusions

Based on our findings, we can conclude that there needs to be more discussions about indexicality and societal attitudes towards celebrity culture. Our study found that female interviewees are more likely to receive personal and invasive questions compared to their male coworkers. We observed that interviewees have various strategies to navigate these invasive questions, such as using humor or redirecting the conversation. This finding aligns with our hypothesis and suggests that gender does play a significant role in the nature of questions asked in celebrity interviews.

When comparing our own study with previous research, we can view consistent results with Rossi and Stivers, Tavits and Perez, and Wood. They show that female celebrities often face questions that cross personal boundaries, contributing to the systemic stereotyping and underrepresentation of women in the media. Interestingly, in the Tavits and Perez article, they found that “the effects of feminine pronouns parallel those of gender-neutral pronouns: both heighten the salience of non-males in memory, which is then associated with people expressing more liberal opinions toward women and LGBT groups in politics” (Tavits and Perez, 2019). This article informs us of variables that affect how a viewer might perceive the interactions captured in celebrity interviews. To continue, Wood’s article on gendered media can help us to better see the media’s representation of men, women, and queer people and how that may affect a viewer’s understanding of gender roles (Julia T. Woods, 2013). Interviews play a greater role in what is acceptable and what is normalized amongst gender groups.

Our study suggests that the media continues to reinforce traditional gender roles by subjecting female celebs to more personal scrutiny. Wood did a great job at explaining this. She stated how “depictions of relationships between men and women emphasize roles and normalize violence against women” (Wood, 2013). This not only affects the celebrities themselves but also influences public perceptions of acceptable behavior towards different genders. Everything we do in the media gets translated and put into practice outside of the media. So, whatever we allow to happen online will be manifested in real life interactions.

We focused on American celebrities, but if we were to dive into other environments, we would have more evidence to contribute and offer more indications to analyze gender dynamics in media interactions. For the future, we could expand on our study by examining a more diverse range of celebrities, locations, and interview formats.

When we look at our findings holistically, we can understand how the media plays a huge role in shaping public discourse around gender. When we examine the patterns within celebrity interviews, we can see there is a large need for more equitable and respectful media strategies. In our findings, we want to emphasize and analyze these dynamics because they are crucial for social change. It is important to challenge changing media practices so they can better promote gender equality and respect for all individuals in any field of work.

In conclusion, our study not only contributes to understanding media and gender but also calls for a more conscientious and equitable approach to media representation. The media we consume online does not exist in isolation. It shapes our perceptions and behaviors in several tangible ways. Gender biases and stereotypes reinforced in digital content can manifest in real-life interactions. By promoting respectful and equitable interactions online and through interviews, we can adopt more inclusive and respectful behavior towards all genders in our everyday lives, professional or not.

References

Montiel, A. V. (2014). Media and gender a scholarly agenda for the Global Alliance on Media and gender. United Nations Educational, Scientific, and Cultural Organization.

Pewsey, G. (2021, July 13). The world owes Megan Fox an apology. Grazia. https://graziadaily.co.uk/celebrity/news/megan-fox-michael-bay/.

Rossi, G., & Stivers, T. (2020). Category-sensitive actions in interaction. Social Psychology Quarterly, 84(1), 49–74. https://doi.org/10.1177/0190272520944595.

Tavits, M., & Pérez, E. O. (2019). Language influences mass opinion toward gender and LGBT equality. Proceedings of the National Academy of Sciences, 116(34), 16781–16786. https://doi.org/10.1073/pnas.1908156116.

Wood, J. T. (2013). Gendered Media: The Influence of Media on Views of Gender. Chapel Hill, NC; Department of Communication, University of North Carolina at Chapel Hill.

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“Swag Toh Dekho:” Hindi-English Code-Switching in Bollywood Movies of the Last 30 Years

Krithi de Souza, Kara Bryant, Sophia Adams, Medha Kini

Bollywood! We know (and love) the films for their grand and magnificent dance sequences, epic love stories, and extra long running times. Bollywood is often referred to as the “Indian Hollywood,” and this Hindi cinema industry has a large fanbase of its own. But how much overlap is there between Bollywood and Hollywood? Is there a strong language barrier that separates them? If you’ve watched a modern Bollywood movie, you would know that English words are often scattered throughout the script or used for funny catch phrases and apologetic remarks. But has that always been the case? In our project, we analyze the code-switching in three different Bollywood movies — Kuch Kuch Hota Hai, Student of the Year, and Rocky aur Rani Kii Prem Kahaani — all made by the famous filmmaker, Karan Johar. Each movie was released in a different decade, and we wanted to know how code-switching in Bollywood movies has changed as time passed. Read more to find out about the patterns we observed as the movies became more recent!

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Introduction and Background

In this project, we decided to focus on changes in code-switching from the 1990s onward in order to analyze how globalization and other factors have impacted screenwriting in Bollywood. Hindi-English code-switching has been a part of Indians’ vernaculars for over a century. Far before the advent of the internet age, British colonial rule led to English being incorporated into Hindi to indicate prestige and education (Rai, 2009). Then, as globalization increased over the last 30 years, particularly through the development of the internet as a global resource, more and more Indians gained access to English content through online means. In addition to formalized English education, the population increasingly consumed media produced in English. This came in the form of professionally developed productions such as English-language movies and television, as well as informal, interpersonal content such as social media videos coming from YouTube, Tiktok, and more. Moreover, the Indian economy liberalizing in 1991 brought more access to things such as satellite TV, social media, and other global market products (Kumar, 2013). All this likely affected how often characters code-switched in Bollywood movies.

Our hypothesis is that code-switching will increase overall as the year of release for the films progresses. In other words, as time passes, code-switching will occur more often and become more prevalent in the films as a result of increasing globalization and access to English media. To measure this, we have chosen three Bollywood movies that were produced across three decades — Kuch Kuch Hota Hai (KKHH) (1998), Student of the Year (2012), and Rocky aur Rani Kii Prem Kahaani (Rocky aur Rani) (2023) — to analyze. They are all written by the same screenwriter, Karan Johar, in an attempt to eliminate variables across different filmmakers’ tastes. They all also come from roughly the same genre, romantic comedies, for the same reason. We will use this data to draw conclusions about how much exposure the effects of globalization had on the Bollywood industry. Furthermore, we will be able to say how English use in Bollywood films reflects English use in different populations within India in real life.

Figure 1. Movie posters from KKHH, Student of the Year, and Rocky aur Rani.

Methodology

Based on existing research, we found many different ways to categorize code switches in movies. Our data collection was modeled after a study done on code-switching in three Bollywood movies from three different decades (Anttila, 2015). We categorized the code-switching into two different types: proper code-switching and loanwords. Loanwords are what we define as phrases that were otherwise incorporated into a Hindi matrix sentence, such as the sentence “तु नहिइ  educated है” or “tuu nahiiN educated hai” (Translation: “You are not educated”). “Proper” code-switching as we are defining it for this research project occurred when characters included full phrases or sentences in English, such as “How are you?” (Bali et. al, 2014).

Watch this short clip to see an example of code-switching in Rocky aur Rani.

Each film was watched by at least two members of our team to minimize errors. While watching the movie, every instance of code-switching by the main characters was tallied into one of these two categories. When multiple instances of English words were uttered in a phrase, we used our best judgment to determine its categorization. We only tallied the code-switching of two to three main characters per movie to minimize variables across character type (age, class, education) and maintain a reasonable scope for project.

Results and Analysis

The oldest movie, KKHH, focuses on a best friend duo. Between those two main characters, they produced 13 loanwords and 58 proper code switches, for a total of 71 code switches overall. The next movie, Student of the Year, was released 14 years later. We counted 193 loanwords and 135 proper code switches across three main characters, or 328 code switches overall. Lastly, Rocky aur Rani came out 12 years after that and had 328 loanwords and 290 proper code switches between two main characters, totaling 618 overall code switches. The total number of code switches across the three movies can be visualized in the bar graph below:

Figure 2. Total number of code switches.

Given the data, our hypothesis was correct. The amount of code switches steadily increased across all three movies. Notably, we focused on one fewer protagonists in Rocky aur Rani, yet it still almost doubled the number of total code switches. Thus, we see that over the last 30 years, English usage in Bollywood movies has gone up considerably.

There were several patterns we noticed while analyzing the code switches. Many of the most common instances of code-switching came from characters using popular English phrases, such as “thank you,” “I’m sorry,” or “you’re welcome.” All of these were considered proper code switches for the purposes of our study, although there was some debate of whether they should be considered a single loanword unit because of how they were tied to one meaning. For example, we never saw a code switch like “thank आप,” or “thank aap” (Translation: “thank you”).

One of the biggest changes we noticed over the years was the use of Hindi-English code-switching in songs. Most Bollywood movies are musicals regardless of genre. Music is inherent to the industry, and we counted code-switching in the lyrics of songs the same way we counted spoken lines of dialogue. KKHH has eight songs, Student of the Year has seven, and Rocky aur Rani has eleven. KKHH had no code-switching in the songs. Every song was sung exclusively in Hindi. Student of the Year had slightly more code-switching in the songs, particularly in Shanaya’s entrance song, “Gulabi Ankhen,” which included many brand names. Additionally, there was one song titled in English, “The Disco Song.” Although the title is not an exclusive indicator of English use in the song itself, it does reveal a trend that English was becoming more accepted in the music side of Bollywood. This pattern continued with Rocky aur Rani, which had two songs with some English in the title: “What Jhumka?” and “Heart Throb.” More importantly, the content of the songs throughout the movie had regular code switches. It appears that songs are more resistant to incorporating English, since KKHH had code-switching in dialogue but not songs. However, by 2024, English was heavily included in Bollywood song lyrics. code This may be related to Shet (2022)’s findings that code-switching in film songs signifies purpose in discourse rather than for “aesthetic” purposes like in dialogue.

Another pattern was the use of brand names as a form of code-switching. Given that English can be a signifier of prestige, this effect is heightened when the code-switching indexes luxury items. Characters in Student of the Year and Rocky aur Rani regularly referenced brands such as Louis Vuitton, Ferrari, Jimmy Choo, and Versace. The character Rocky in Rocky aur Rani did this the most consistently. His character is upper class and frequently mentions his possessions by brand name. Interestingly, his code-switching often indexes a superficial, vapid personality as a result. This counters what Antilla (2015) found in her assessment, that English had become a language of professionalism and accomplishment. Rocky frequently uses English slang, but since he uses it haphazardly and without formal education, he is sometimes considered an idiot by those around him. Therefore, we can surmise that not only is the amount of English code-switching changing, but that its meaning in Bollywood is changing too.

Both code-switching in songs and use of brand names can be seen in the example below, which shows three lines from the verse of the song “Heart Throb” in Rocky aur Rani.

Figure 3. Lyrics from “Heart Throb”

In just this excerpt, lasting six seconds in the song, there are five loanwords: “swag,” “heart throb” twice, “Prada,” and “Gucci.” The line roughly translates to “Look at the swag, it’s like Prada and Gucci gave birth to a son.” Thus, we see Rocky using English slang (“swag,” “heart throb”) and brand names (Prada, Gucci) to signify coolness and style.

Discussion and Conclusion

Our analysis of our three films — Kuch Kuch Hota Hai, Student of the Year, and Rocky aur Rani Kii Prem Kahaani — show a clear trend of increasing code-switching. Since these three films came out in sequential decades following the explosion of the internet age and social media usage, the data supports our hypothesis that globalization and media exposure are driving forces behind these changes. Each film demonstrates a greater frequency of English phrases and loanwords, suggesting that modern day Bollywood films are catering to an audience that is more familiar with an inclusion of English.

However, there are several limitations to our study. In future research, it would be helpful to have access to the scripts, so we can accurately count the number of code-switches used in the films. Our method of manually tallying code-switching instances while watching the movies might not have captured every instance accurately. Having access to scripts that we could read would provide a more precise count and better context for each instance of code-switching. Additionally, we focused on three films from a single filmmaker, which might not fully represent broader trends across the industry.

Future research could address these limitations by expanding our method to include films from various filmmakers and genres and collect data from multiple characters, not just the protagonists. Furthermore, it would be beneficial to perform research confirming the correlation between code-switching in Bollywood and English usage in real life. We could do this by exploring the perception of English among viewers who recently finished watching Bollywood movies. Researchers can also analyze if non-English speakers’ perception of English changes after watching a Bollywood film due to the presence of code-switching between Hindi and English. Another possibility would be to compare native Hindi speakers’ code-switching with that of the fictional characters to see if the frequency is comparable. This would be one way to determine whether Hindi-English code-switching changes when it is scripted versus non-scripted. Therefore, due to this research, researchers can discover the impact code-switching has on society.

Since our research project effectively replicated Anttila (2015)’s project studying three movies from 1988, 1996, and 2005, it will be interesting to see if the use of Hindi-English code-switching will continue to trend upward. Anttila found that code-switching increased over time across her three movies, just like we did. But if this study were performed again another ten years from now, will English in Bollywood movies continue to increase or will it eventually stagnate? Is there a “saturation point” for English usage? At a certain point, the question becomes when is the movie itself “bilingual” rather than the characters?

In conclusion, analyzing Bollywood movies can help assess how English is perceived and used in India. The findings suggest that English is steadily increasing across Bollywood. Since media is a reflection of its society, we can conclude that English access is increasing overall in India, thus reflecting trends of a globalized society and proliferation of digital media. This increase in code-switching suggests that English is becoming more ingrained in everyday society in India, not just as a symbol of prestige but also as a tool for communication. Due to the creation of the Internet and the rise in social media, there is now greater access to English across India. These platforms provided greater access to English content in the media. This creates a positive feedback loop because as more people use the Internet, their exposure to English increases, encouraging them to adopt English in their vernaculars, which in turn exposes more people to English. Our research project highlights the increasing presence of English in Bollywood films, reflecting broader societal changes driven by globalization and digital media.

References

Anttila, H. (2015). You come-come, memsaabCode-switching in Sherni (1988), Raja Hindustani (1996) and Dus (2005) (Publication No. 6357) [Master’s Thesis, University of Vaasa]. OSUVA Open Science.

Bali, K., Sharma, J., Choudhury, M., & Vyas, Y. (2014). “I am borrowing ya mixing?” An analysis of English-Hindi code mixing in Facebook. Proceedings of The First Workshop on Computational Approaches to Code Switching, 116-126. https://aclanthology.org/W14-3914.pdf.

Kumar, A. (2013). Globalization and Changing Patterns in the Hindi Cinema Industry. Journal of South Asian Studies, 29(2), 433-448

Rai, A. (2009). English in Postcolonial India: History, Politics, and Cultures. Oxford University Press.

Shet, J. P., & Premkumar G. (2022). To switch and mix or not to: Code switching and code mixing in Indian film songs. Journal of Positive School Psychology, 6(3), 1417-1430. https://www.journalppw.com/index.php/jpsp/article/view/1672.

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Media & Reality All at Once: How ‘Everything Everywhere All at Once’ is doing its best to exemplify our code-switched conversations

Jacqueline Aguirre, Josiah Apodaca, Kaitlyn Khoe, Mason Uesugi, Wonjun Kim

Code-switching, or the use of more than one language, dialect, or code in an utterance or conversation, can be a way to signal identity. This study compares two sources of code-switching — conversations from media, specifically Everything Everywhere All at Once (2022), and conversations in real life — by categorizing utterances and types of code-switching. This study investigates the representation of code-switching in bilingual media and the similarities and differences to code-switching in daily life. The real life conversations were conducted with Mandarin-English bilinguals, and the two conversations ran for 8 and 10 minutes. The findings demonstrated that intersentential switching occurred more often in this particular media, while intrasentential switching was preferred by the real-life speakers. The various types and functions of code-switching were present in the media, which was expected given the larger sample size and production resources and timelines. Nonetheless, both case studies demonstrated significant levels and mannerisms of code-switching, aligning with the proposed variables and categories. Further studies could utilize other syntactic properties, pitch contours, and tonal articulations in order to auditorily represent accuracies and behaviors of code-switches as more bilingual media makes its way into the American entertainment landscape.

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Introduction and Background

Code-switching (CS) refers to when a speaker alternates between two or more languages, or language varieties, within a single sentence or interaction. Code-switching is a linguistic function mostly used in bilingual speech communities to convey a mutual “in-group” status between speakers, as the ability to code-switch demonstrates proficiency in both of the utilized languages. Our study seeks to answer these questions: How is code-switching represented in media? What are the differences and similarities to code-switching in everyday life?

Deriving from the studies conducted by Shen, Gahl, and Johnson on English-to-Mandarin code-switches, we compared the types of code-switching between Mandarin and English in media, through the 2022 film Everything Everywhere All at Once (EEAO), versus real life to see how accurately code-switching is being represented. The aforementioned study by the researchers suggest the existence of “switch cost,” as the English-Mandarin bilinguals consistently displayed slower reaction times specific to the code-switches in sentence-medial positions, as highlighted in their eye tracking experiment (Shen et al,. 2020). However, while there are many studies giving structure to code-switching, there are fewer applying them to media. 

Our target population for this project were Mandarin Chinese and English bilingual speakers. Mandarin Chinese belongs to the language family of Sino-Tibetan languages, which is under the Sinitic branch (Odinye 2015). Internationally, about 1.3 billion people use the language, being the official language of China and Taiwan (Odinye 2015).

Figure 1. Explanation and examples of code-switching types.

There are three different types of code-switching: tag-switches, which are exclamations, parentheticals or an aside in another language than the rest of the sentence; intrasentential switches, which occur in the middle of the sentence and are typically called code-mixing; and intersentential switches, which occur between sentences (Appel & Muyusken, 2006). We will use these categories in our data analysis to see if some forms of media uphold current code-switching practices.

Figure 2. Explanation of code-switching functions.

Code-switching in a sentence can also serve different functions depending on the speaker, topic, and context of the language used. Researchers Appel & Muyuskend determined six categories as follows: (1) referential, where some subjects or words are more apt for one language, perhaps due to a lack of knowledge; (2) directive, to exclude or include the hearer; (3) expressive, emphasizing mixed identity; (4) phatic, or metaphorical switching; (5) metalinguistic, to comment indirectly or directly on the languages involved; and (6) poetic, which are switched puns or jokes (Appel & Muyusken, 2006).

There is going to be a lot left out about the filmmakers here, but in terms of context about the media that is relevant to code-switching, one of the writer/director duo ‘the Daniels,’ Kwan, is a second-generation Chinese-American. Having been in a Chinese Mandarin and English home environment, he is likely comfortable with engaging in code-switching because of his multilingual parents. One of the producers, Jonathan Wang, hopped on this project also because he wanted to tell a story inspired by his own immigrant parents, so he likely had a hand in ensuring language accuracy, like with the Cantonese, alongside with several translators. With this background in mind, we hypothesized that the movie’s representation of code-switching should be fairly accurate to how speakers code switch in real life.

We hypothesize that the participants and the script should have similar examples and amounts of code-switching in type and function within the given environmental parameters, as established earlier. Our research will help determine whether change is needed in how bilingualism is being represented, or if there is already a solid structure in place for new media to follow.

Methods

Figure 3. Step-by-step breakdown of our methodology.

Our project design comes in two parts: analyzing the media and analyzing a conversation in real-life. The script had both lines as they were spoken along with translations, so we could categorize them based on type of CS. We applied that same process to two conversations, around 10 minutes each, recorded between two sets of participants. They did know they were being recorded but eventually seemed to forget (over a period of around 10 minutes for each set), so the conversation seemed to flow naturally, with them code-switching subconsciously.

Figure 4. Language background of participants and EEAO characters.

We then analyzed the two sources of code-switching and made comparisons. For the screening process, we found our participants based on a language background survey collecting information, such as their L1, L2, and how they acquired their L2, as shown above. The characters’ method of L2 acquisition and L3 is speculated based on context. It is also likely that Evelyn is a simultaneous bilingual in Cantonese and Mandarin. Only the L2 acquisition method is listed, as it is relevant to our focus on bilingual speakers. Two of the participants (John and Daniel) were close cousins to reflect, while not exactly, the close relationship between Raymond and Evelyn. We also had one of them talk to their own mother to see if there would be a change with the different social dynamic. 

Results and Analysis

The table below shows the tallies for the types of code-switching used in the EEAO script (the blue indicating code-switching in media) and the conversations recorded with our participants (green for real-life code-switching). Since the conversations were not exactly the same amount of time, the proportions for each type of CS were calculated by dividing the total for each conversation by the count. There was insignificant information for tag switching in both the script and recordings, so it was left out of the table.

Figure 5. Code-switching frequency in media vs. recorded conversations. Proportion represents type of code-switching used in conversation out of total occurrences of code-switching.

Waymond and Evelyn used intersentential switching more than intrasentential (30 versus 14 times). That pattern is the same for Daniel and his mother (15 versus 11 times), while Daniel and John opted for more intrasentential switching (6 versus 21 times). The type of CS (intrasentential) that is more common for Daniel and his mother, whose language background and fluency matches best with EEAO characters, is the same as in EEAO conversations.

As for functions, each pair (Daniel and John, and Daniel and his mother) were dominant in the referential function, where some words or phrases are more easily expressed in one language. This outcome is likely because of the speakers’ proficiency in their second language — Mandarin. In a self-reported survey, both Daniel and John rated their L2 proficiency as a 3. The expressive and poetic function appear in the recorded conversations (CS was also used to repeat and clarify). The directive function likely does not appear in these conversations because they were recorded in isolated, controlled environments. Had they been in more natural environments, out in public, it is likely that the directive function would appear.

As for the functions present in the EEAO conversation, they were also dominant in the referential function of code-switching, with directive being the second most used. Considering the characters, Waymond and Evelyn, immigrated to America and were likely not exposed to their L2 (English) until later, it makes sense that the referential expression is dominant for them as well. Regarding their use of the directive function, this is most likely due to Waymond and Evelyn being in various environments where there was a third-party to exclude or include (e.g., customers, Gong Gong). Additionally, unlike our speakers, the expressive function does not appear in the movie, but the poetic function does show up once. 

Based on these results, it seems that the code-switching in EEAO supports the theory of the different types and functions of code-switching. When comparing our speakers’ code-switching with the movie, both align in having referential code-switching be primarily used in communication. Though with our speakers, they showed slightly more variety in function, as they covered expressive functions while the movie did not. While the movie significantly used the directive function, our speakers did not. Again, we conclude that this is due to a difference in environments between the speakers.

Discussion and Conclusion

The data promotes the idea that EEAO and its representation of code-switching is accurate. Since Daniel’s code-switching varied based on the hearers (with his cousin versus his mother), the movie’s representation is also accurate in representing how code-switching is employed for differing functions based on environment.

While the conversations and media we analyzed ended up with similarities, affirming our hypothesis of EEAO being an accurate representation of code-switching, further research is needed to extend these results to media in general. After studying natural conversations of English-Mandarin bilinguals, researcher Xitong Zhang found that “the occurrence of code-switching not only depends on the language ability of the speaker, but also the purpose and the environment in which the conversation occurs” (Zhang, 2019, p. 44). One of the ways to expand this study in the future would be to observe participants in more environments and situations over longer periods of time (e.g., recording conversations over the course of a week) because EEAO has more environments. This choice would provide more data for analysis and allow for a richer case study of CS.

It would also help to have participants whose language background better matches the characters even better because Daniel and John did not have the same L1/L2 as Waymond and Evelyn. However, the time constraint of this study provided a limited participant pool to see how identity and linguistic competency affect code-switching.

We could also look into instances of “bad” code-switching in media, likely tied to older media sources, to develop concrete standards of accurate code-switching — including what not to do — for future representations of the bilingual experience. We could just look at more films, maybe in other language pairings, or other sources of media, like TV shows, whether good or bad examples, as well.

In his video essay “English. Language. Movies. Parasite,” Kyle Kallgren studies code-switching in the 2019 film Parasite and the cultural implications of mixing English and Korean in conversation. The Parks, a rich family, often uses English to confide in each other or to establish solidarity with their hired workers. It seems that English is worked into the plot accents, signifying the divide between the poor and rich families. In a similar fashion, language boundaries reinforce relationships in the plot of EEAO, with code-switching being a big part of it.

America tends to fawn over foreign culture without realizing it is their own culture being sold back to them — just accented — which is probably why they find connection to it. There is something to be said about how these two movies employ code-switching as a tool to hint at language hierarchies. Studying the use of language and code-switching in media like this is important for providing a foundation for how to approach appropriate representation in media. There are harmful social implications if one does not consider the influence of how language is used in movies. As language hierarchies exist in reality, noticing and replicating them in media will only reinforce them when they should be dismantled. Understanding how media perpetuates practices in which social classes are tied to certain manners of speaking can help us counteract that.

 

References

Anindita, K. (2022). An Analysis of Code-Switching in the Movie “Luca”. ELTR Journal, 7(1 23-33. https://doi.org/10.37147/eltr.v7i1.164

Appel, R. & Muysken, P. (2006). Language Contact and Bilingualism. Chicago: University of Chicago Press.

Chen, Z., & Liu, X. (2023). Types and Functions of Code-Switching in the Film Everything Everywhere All at Once. Journal of Education, Humanities and Social Sciences, 13, 171-176. https://doi.org/10.54097/ehss.v13i.7889.

Kwan, D. and Scheinert, D. (Writer). (2022). Everything Everywhere All at Once. A24.

Odinye, S. I. (2015). Phonology of Mandarin Chinese: Pinyin Vs. IPA. Quarterly Journal of Chinese Studies, vol. 4, no. 2, p. 51–58.

Reformadita, A., & Setyaji, A. (2021, October). Code-Switching Analysis on Pixar’s “Coco” Movie. In Undergraduate Conference on Applied Linguistics, Linguistics, and Literature. (Vol. 1, No. 1, pp. 26-37).

Shen, A., Gahl, S., & Johnson, K. (2020). Didn’t hear that coming: Effects of withholding phonetic cues to code-switching. Bilingualism: Language and Cognition, 23(5), 1020-1031.

Zhang, X. (2019). Code-Switching in English-Chinese Ordinary Conversations. TESOL Working Paper Series, 17, 38-45.

 

Appendix A

PDF Link for EEAO Script

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