Sociolinguistics

Some Info and Context 

Our study shines a spotlight on the Thai restaurant workers of Westwood, Los Angeles. In the mid-20th century, Thai migration to the U.S grew significantly, and inevitably Thai-owned businesses grew in urban centers (Losavio, 2021). Now, some might say almost every town in America has a Thai restaurant. More specifically though, LA Thai restaurants shape the representation of Thai identity and community (Padoongpatt, 2011). They function as multilingual and multicultural spaces, despite being in a predominantly English-speaking city. LA is a unique location to research Thai people; most of them didn’t immigrate to flee war and were instead seeking opportunities (Losavio, 2021). Most were already middle-to-upper-class people who immigrated for higher education, tourism, or careers. 

Figure 1. Locations of top-rated Thai restaurants in LA, all observed in Thai Town, Los Angeles.

Thailand used food as a tool of cultural diplomacy through gastrodiplomacy in the 21st century. It’s a form of public diplomacy used to communicate culture and identity through national cuisines, often effectively creating brand recognition and expanding soft power abroad (Raksarat 2022). Cuisine is a tool for countries to shape international perceptions in a globalized world. The Thai government created training programs for chefs, financial assistance for restauranters, encouraged Thai investors to open locations overseas, and special visas for Thai chefs. This increased the global visibility of Thai food and stimulated tourism, shifting international perceptions towards a richer identity rooted in culinary traditions (Raksarat 2022).

Padoongpatt (2011) additionally argues that Thai people undermine their racialisation through food, keeping a distinct identity from other Asian cultures, but also that Thai cuisine is used to establish racial boundaries by white people and that their quest for “exotic” cuisine is ultimately rooted in colonialism and U.S. imperialism. Thai cuisine began to gain popularity in richer white neighborhoods, but it remained dependent on frequently exploited workers with their own hierarchies. These might overlap with Thai cultural norms’ emphasis on respect, age-based hierarchy, and relational harmony. We examined Thai-English code-switching and politeness strategies in restaurant settings shaped by context — norms may be different in multicultural service compared to the average American priority of being direct and friendly. 

What Did We Decide To Do?

The rundown: we looked at three different Thai-owned restaurants in LA, California: Sanamluang Cafe in Thai Town, Emporium Thai in Westwood, and Mr. Noodle in Westwood. Thai Town is one of the two federally recognized Thai Towns in the US. It serves as a Thai cultural enclave and has the largest number of Thai residents outside of Thailand. Westwood is a neighborhood in West LA and is the home of UCLA, with many affluent neighborhoods bordering it. 

We visited all three restaurants in person and took notes of our observations of communication styles with ourselves as English-speaking customers. At Emporium Thai, staff spoke only English with us. The server greeted us with “How are you doing?” and later said, “I like your top.” At Sanamluang Cafe, staff interaction was brief and direct, such as asking “How spicy?” and giving options like “Mild, Medium, Spicy.” Conversation was minimal. At Mr. Noodle, staff interactions were more personal than Sanamluang, but less conversational than Emporium Thai. Our server checked in with “Is everything ok? For to go?” and later “Everything ok na?”. Staff interacted casually with customers.

In surveys, we asked questions about comfort level speaking English and Thai, in or out of work, and with customers or other staff. Questions regarding proficiency in English were rated on a scale of Very Poor, Poor, Average, Good, and Very Good. Questions on the frequency of speaking in English or Thai were rated on a scale of Never, Rarely, Sometimes, Often, Very Often. Questions regarding comfort level speaking English or Thai to customers or staff were rated as Yes, Neutral, No.

We also looked at the menu language of each restaurant and compared how they describe the same dishes. For example, the dish ส้มตำ or /sôm tām/ – Thai papaya salad. On Sanamlaung’s menu, this dish is written in Thai as “ส้มต่ำ ตลาด อ.ต.ก.,” which translates to “Papaya Salad from Or Tor Kor Market” (a famous market in Thailand), and listed in English as “SOM TUM” (the English transliteration). However, on Emporium Thai’s menu, this dish is listed as “Papaya Salad Vegan.”

Figure 2. Side-by-side comparison of menu language from Emporium Thai and Sanamlaung Cafe. Thai Town restaurants appeal to a Thai-speaking audience, while Westwood restaurants use descriptive English names.

Lastly, we recorded and transcribed a naturally occurring interaction between a Thai-speaking customer and two non-Thai diners at Mr. Noodle. The transcript was analyzed line-by-line to identify instances of Thai–English code-switching, and shows how the conversation switches between English and Thai based on who the server is talking to in the group.

So, What Did We Find?

Survey responses from two staff members at Mr. Noodle suggest that both Thai and English are used in the workplace, but English is primarily used when interacting with customers. As seen in Figure 3, they reported comfort speaking English and described the dominant customer demographic as “Americans,” suggesting that English is the primary service language in restaurants serving mostly non-Thai clientele.

Figure 3. Staff-reported comfort in English language use at Mr. Noodle. English is used more comfortably with customers, while Thai is used more in staff interactions.

These language choices can be understood through “audience design”, where language is adapted depending on the expected audience. Restaurants serving mostly non-Thai customers have menu language to make dishes more familiar to Westerners. At the same time, these choices may reflect the commodification of culture, elements of Thai cuisine repackaged to be Westernized.

Figure 4. Lines 7 and 8 from transcript. Example of Thai–English code-switching during ordering. The speaker switches languages within a single utterance and the waiter continues in English when addressing non-Thai diners.

To further support this pattern, the transcript from Mr. Noodle shows a waiter switching between Thai and English depending on who they are addressing (Figure 4). The waiter speaks Thai with the Thai-speaking customer but switches to English when communicating with other diners, particularly when discussing spice levels. This suggests that the Thai-speaking customer acts as a linguistic intermediary between staff and other diners. 

Field notes also show differences in interactional style across restaurants. At Emporium Thai, staff used more positive face strategies, while interactions at Sanamluang used negative face strategies. Restaurants serving mostly non-Thai clientele tend to use more English and culturally adapted menu descriptions of Thai dishes, while establishments in Thai Town retain more traditional Thai terminology. This suggests that language choice and interaction style shift depending on the expected customer base, highlighting how restaurants adapt linguistically to their surrounding communities. Overall, code-switching functions as a practical and social strategy, helping workers navigate cultural expectations, communicate effectively, and adapt Thai identity to diverse audiences.

Food For Thought

Mr. Noodle appears to occupy a middle position between these models. Based on our notes, Mr. Noodle seems to cater more toward Asian or Asian-American customers, incorporating several pan-Asian items. The restaurant lists “Hainan Chicken” rather than the Thai name “Khao Man Gai,” which may make the dish recognizable to a broader audience. Interaction styles also fell between the other two restaurants: staff interactions had less positive face than at Emporium Thai but more conversational exchanges than observed at Sanamluang. Our transcript also shows staff switching between languages depending on the customer, suggesting that the restaurant navigates multiple linguistic and cultural audiences at once. Though Emporium Thai and Mr. Noodle are both in Westwood, our findings suggest there can still be stark linguistic differences in customer-staff interactions tied to the specific demographic of the restaurant area, demonstrating a wide range of linguistic flexibility within one neighborhood. Our theory is that since the location of Mr. Noodle is very close to UCLA and its diverse population, it influences the language used. Emporium Thai is located further, and the language used by staff could be influenced by the demographics of the predominantly White surrounding areas.

This linguistic flexibility shows a willingness to adapt to different environments and market Thai culture to different audiences. The history of Thai immigration may allow Thai immigrants more flexibility to adapt to Western audiences, confident in the preservation of their culture. The claim that Thailand was the “only South East Asian country to avoid colonization from a European power” created a sense of exceptionalism and national pride (Losavio, 2021). When there is less concern for survival and preservation, it typically follows that there is less concern for loss, as perhaps showcased by Thai immigrants’ willingness to adapt and blend for a higher Western appeal.

Bibliography

Bailey, B. (1997). Communication of respect in interethnic service encounters. Language in Society, 26(3), 327–356.

Half as Interesting. (2021, December 22). Why Almost Every Town In America Has a Thai Restaurant. YouTube. https://www.youtube.com/watch?v=W09QCLmnCUU  

Losavio, J. (2021). Temporary Thais: Circular Thai–US Migration in the 1960s. Journal of American Ethnic History, 40(4), 41–85. https://doi.org/10.5406/jamerethnhist.40.4.0041

Padoongpatt, T. M. (2011). Too hot to handle: Food, empire, and race in Thai Los Angeles. Radical History Review, (110), 83–108. https://doi.org/10.1215/01636545-2010-027 

Prin, N. (2021). A case study of code-switching among Thai waiters in a Cambridge, UK restaurant. MANUSYA: Journal of Humanities, 24, 106–125. https://doi.org/10.1163/26659077-02401004 

Raksarat, N. (2022). THE ORIGINS AND DEVELOPMENT OF THAILAND’S  GASTRODIPLOMACY https://ethesisarchive.library.tu.ac.th/thesis/2022/TU_2022_6203120016_17855_27618.pdf

Tritle, H. L. (1996). To Switch or Not to Switch: Using Hymes’ SPEAKING Model to Analyze Code-Switching in a French Restaurant. Ohio Working Papers in Linguistics and Language Teaching, 15(fall), 77–84.

Young, H. (2022). Code-Switching: Patterns and Motivations for Thai American Code-Switching: Patterns and Motivations for Thai American Bilingual Speakers. https://huskiecommons.lib.niu.edu/cgi/viewcontent.cgi?article=2432&context=studentengagement-honorscapstones 

Zhang, Z. (Victor). (2024). Identity Construction and Second Language Acquisition: A Multiple Case Study of Thai Immigrants in Hong Kong. Journal of Language, Identity, and Education, 23(4), 498–511.https://doi.org/10.1080/15348458.2021.1999816

Introduction

Language is one of the most immediate signals people use to form impressions of others. Within seconds of hearing someone speak, listeners often make assumptions about a speaker’s background, intelligence, education, or social status. In England, where regional accents are closely tied to class and geographic identity, these perceptions can carry particularly strong cultural significance. Accents such as Received Pronunciation (RP), Cockney, and the West Country accent have long been associated with different positions within England’s social hierarchy, shaping how speakers are perceived in professional, educational, and social contexts (Fraser, 1988).

Previous research has consistently found that RP is often associated with prestige and competence, while more regionally marked accents are sometimes evaluated less favorably (Wongkittiporn, 2024). However, less attention has been given to whether listeners separate judgments of a speaker’s ability from their sense of whether that speaker’s voice aligns with socially expected identities of authority, status, or belonging. These perceptions may also reflect deeper assumptions about how speakers see themselves and how they are expected to fit within broader social hierarchies.

Background

One way to understand accent bias in England is to look at how certain ways of speaking became linked to power in the first place. Over time, institutions like schools, government, and media helped establish which accents sounded “professional” or authoritative. These associations were not based on linguistic correctness, but on who was using those accents and in what contexts (Wongkittiporn, 2024). Received Pronunciation (RP) is a good example of this process. It became associated with elite education and national broadcasting, which gave it a reputation for sounding credible and intelligent because it is found “to be most dominant in the areas of South East England which are most populated by the highest socioeconomic classes” (Cole, 2021).

In contrast, accents like Cockney and West Country English developed very different associations. Cockney is tied to “the white working class in East London”, while West Country English is linked to rural areas in the southwest (Cole, 2021). Because of these social and geographic connections, they are often perceived as less formal or less professional, even though there is nothing linguistically inferior about them.

Methods

This study examined how individuals from England perceive their accents and how these perceptions influence their speech in various situations. There were two groups: the interview group and the outsider group. Participants in the interview group consisted of 3 college-aged adults who were either born in England or had spent a significant amount of their lives there, ensuring familiarity with different accents. Participants came from different regions and ethnic backgrounds, allowing for variation in accent types and experiences. The outsider group consisted of 15 individuals born or raised outside of England and was used to examine outsider perceptions of accents within England.

Data were collected through virtual interviews and an online perception survey. Participants in the outsider group completed an online, audio-based survey where they listened to 20-second speech clips of different English accents: Cockney, Received Pronunciation, and West Country. After each clip, participants rated the speaker on various social factors such as status, friendliness, and intelligence. This helped establish that accent-based hierarchies exist, which were then further explored through interviews with participants from England.

The interview group explored participants’ personal experiences with their English accents, including how it shapes their identity, as well as how it influences their speech in professional and social contexts. Other questions addressed whether participants felt pressured to modify their speech or code-switch due to past experiences with accent prestige and hierarchy. Participants were also asked to reflect on general changes in their regions’ accents over time, including accent leveling and intergenerational differences.

Analysis focused on identifying themes in participants’ self-reflections on their accent, its role in identity, and how they adjust their speech across contexts. Specifically, we examined patterns in participants’ descriptions of accent stereotypes, accent-based judgments, and the role of accent in shaping social and professional interactions.

Findings

The survey asked outsider participants to rate RP, Cockney, and West Country speakers across four traits on a 1 to 7 scale. On perceived education and status, the results aligned with existing assumptions about English accent hierarchies. RP speakers scored highest on education (5.87) and status (5.0), Cockney fell in the middle (5.13 and 4.27), and West Country scored lowest on both (3.0 and 2.53), nearly three full points below RP on education alone.

Figure 1. Perceived education level by accent, with RP rated highest, Cockney moderate, and West Country lowest on a 1–7 Likert scale.

The more revealing results came from trustworthiness and approachability. West Country speakers scored highest on approachability (5.6) and nearly matched RP on trustworthiness (5.53 vs 5.4), despite their low education and status scores. Listeners make distinct judgments depending on the trait in question, and regional accents, while penalized on markers of competence, can actually outperform prestige accents on markers of warmth.

Figure 2. Perceived trustworthiness by accent, with West Country rated highest, RP moderate, and Cockney lowest on a 1–7 Likert scale.

The interviews added an important personal dimension. Charlotte, our RP speaker from outside Oxford, described RP as “just the default” growing up, an assumption that shifted when a manager told her she “sounded competent” before her interview had even concluded. Yet she also noted that people would “stiffen up” when she spoke in meetings. The two participants with hybrid accents described a different experience entirely, one noting that speaking formally meant being “taken more seriously,” while the other characterized her speech adjustments as both “strategic and subconscious.” For these participants, accent required active and ongoing management.

Impact

Accents in England shapes perceptions of education, authority, and social standing, but it also shapes how speakers understand and present themselves. Every participant demonstrated a clear awareness of the hierarchy around them. Charlotte acknowledged that her accent had “opened doors” she never had to knock on, while also recognizing that it came loaded with assumptions she did not always welcome, including being perceived as “out of touch.” Meanwhile, the participant raised across India and South Africa described a period in his life when he consciously tried to change the way he spoke to fit in socially, something he later described as “disingenuous” to his own identity. These are not abstract observations. They are the lived consequences of a hierarchy that assigns social value to the sound of a person’s voice.

What makes accent-based bias particularly difficult to address is that it is rarely treated as a serious form of discrimination. Accent tends to be framed as something neutral or changeable, which makes it easy to dismiss. But the patterns this study uncovered suggest otherwise. The hierarchy was not something any participant had been explicitly taught. As Charlotte put it, she only became “more aware” of her accent over time and “more critical of what she used to think was neutral.” That gradual, largely unconscious absorption is precisely what makes accent bias so durable. When a prestige accent feels like the default rather than a privilege, the inequalities it produces become very difficult to see, let alone challenge.

References

Cole, A. (2021). Disambiguating language attitudes held towards sociodemographic groups and geographic areas in South East England. Journal of Linguistic Geography, 9, 13–27. https://doi.org/10.1017/jlg.2021.2

Fraser, S. A. (1988). Language and social class in Britain. Social Information Science, 4, 157–172. https://doi.org/10.60171/00005114

Wongkittiporn, A. (2024). Phonological features: Standard British English and the West Countries dialects. Proceedings of the RSU International Research Conference (RSUCON-2024). Rangsit University. https://rsucon.rsu.ac.th/files/proceedings/RSUSOC2024/IN24-025.pdf

Introduction

Artificial intelligence, or AI, has rapidly become part of online culture. Tools like ChatGPT, Claude, Grok, and many more are more commonly being used to assist in the creation of social media content, from editing minute details to generating entire videos. However, research suggests that AI has different patterns of “speech” when compared to humans. For example, one study notes specific words that are overrepresented in AI-generated language, including surpass, align, and exhibit (Anderson et al., 2025). In addition to specific words, AI tends to use more emotionally vibrant language than humans (Markowitz et al., 2024). Despite this research, little is known about whether everyday users can actually recognize these features in social media content. Our research group proposed that these features would be recognizable by humans, whether consciously or subconsciously, and they would then be able to distinguish between AI-generated content and human-made content. Specifically, we expected to see people use certain word choices as evidence that a script was generated by AI. We chose to evaluate college students for this task because many students have had consistent exposure to AI as well as social media content, so naturally, we expected them to be the most reliable in evaluating whether or not a piece of content was scripted by an LLM.

Methods

To test whether people can detect AI in online scripts, we created a survey that was then administered and answered anonymously by twenty-one college students. To prime them for the questions we would ask, we first asked how confident they felt in identifying AI-generated content in general. We then asked what specific markers each person uses to discern whether something is AI-generated and if participants felt that their own speech and writing had been impacted by AI. These questions were intended to get the respondents to think more deeply about how they evaluate content, both AI-generated and human-made.

After this, we showed the participants two TikTok videos (Rutkowski, 2026; Frka, 2025). The first video had markers of AI usage in its word choice; certain words have been shown to be overused by AI (Anderson et al., 2025), one of which is “demographic,” which was present in the first video’s script. The video was also released after 2023, which means that ChatGPT and other LLMs were already being commonly used, and the video’s script could have plausibly
been generated by AI. The second video was also released after 2023 and could have been influenced by AI scripting, but had none of the target words that are most frequently overused by LLMs. The participants were then asked to evaluate whether they thought AI was used to script each video, and if so, what markers of AI they noticed. Both videos that we selected were informal and conversational, positioning the creator as an expert on their specific topic while also maintaining approachability.

Our study was limited by the fact that we only had twenty-one participants who were all in college. We also recognize the limitations of influencers online not disclosing whether their content was made using generative AI, so we have no definitive way to know whether either video was actually scripted with AI. However, since the focus of our research was centered on how people interpret videos regardless of whether AI was actually involved, this issue has no
bearing on the conclusions we reached.

Results

The first question that we asked respondents was how confident they felt in detecting when AI had been used to create social media content. We did not specify any particular type of content or method of AI generation, so this question applies to videos, text-based posts, photos, and speech. Figure 1 shows that most people rated themselves as moderately to highly confident, with 5 being most confident and 1 being least confident. However, when asked about detecting AI specifically in the scripts of videos where a creator is speaking, participants were significantly less confident (Figure 2). None of the people who responded to the survey said that they were highly confident in discerning whether AI had been used to script a video.

We then asked participants to view the two TikTok videos. Figure 3 displays pie charts of the proportion of participants who thought each video’s script was AI-generated. The first video, which did have speech that we know to be overused by LLMs, got mixed responses. Over half of the participants believed that it was scripted by AI, but nearly 43 percent said that it was not. The second video, which did not have markers of AI scripting, was much
less divisive. Nearly all of the participants concluded that it was not AI-generated.

Whenever participants thought that a video was scripted with AI, they were prompted to explain what led them to that conclusion. For the first video, only one participant actually pointed out a specific word that the creator used, that word being “snowball”; all other responses detailed sentence structure and the general flow of the video. In terms of the second video, participants said that the speaker seemed more real, but did not provide reasoning for this opinion. Another question that we asked was whether participants thought that their own speech had been influenced by AI. In keeping with the theme of our hypothesis, we were especially interested in whether participants had noticed themselves using certain words more or less often than they had before the popularity of LLMs. Those who responded that their speech had been changed by AI cited grammar differences, with some saying it was a helpful tool for editing papers and others noting that they avoided certain phrases in order to sound more human. No respondents mentioned any specific words that had entered or left their vocabulary.

Conclusions

Contrary to our expectations, the data collected shows that college students generally do not use specific word usage as indicative of AI writing. However, this does not mean that they have no way of distinguishing between AI-generated and human-made content. Instead of pointing out words, participants looked to phrases and overall sentence structure to speculate on AI language usage. One commented that the language felt overly dramatized, echoing the research and conclusions of Markowitz et al. Another respondent said that the sentences paused or ended in unnatural places. By contrast, those who commented on the second video said that the speaker seemed more authentic without providing any specific examples of how they reached that conclusion.

These findings demonstrate that individuals each have their own criteria for judging whether dialogue is produced by AI; however, these criteria may be based on preexisting biases about how AI or humans are expected to sound. This is especially true of the first video, where participants’ opinions on AI scripting are split nearly in half. Everyone who thought the video was scripted with AI did provide reasoning for their answer, but since the reasons were different, we cannot confidently conclude that there is a “correct” or singular method for individuals to identify when online content creators use AI to write their videos. We can, however, say that our participants have a certain language ideology when it comes to recognizing AI. Rather than pointing to words or features that have already been proven to be overused by AI, participants instead based their responses on assumptions of how they think AI should sound.

Refrences

Anderson, B., Galpin, R., & Juzek, T. S. (2025). Model Misalignment and Language Change: Traces of AI-Associated Language in Unscripted Spoken English (arXiv:2508.00238). arXiv. https://doi.org/10.48550/arXiv.2508.00238 

Frka, C. D. [@PossiblyATherapist]. (2025, December 26). Change is uncomfortable and therapy is about change so there are most likely going to be some periods of discomfort [Video]. TikTok. https://www.tiktok.com/@possiblyatherapist/video/7588290424079486263?q=therapy&t=1770430607744 

Markowitz, D. M., Hancock, J. T., & Bailenson, J. N. (2024). Linguistic Markers of Inherently False AI Communication and Intentionally False Human Communication: Evidence From Hotel Reviews. Journal of Language and Social Psychology, 43(1), 63–82. https://doi.org/10.1177/0261927X231200201 

Rutkowski, G. [@attemptedsoc]. (2026, January 28). this is more context to the other vid i did last week! this idea is SO fascinating to me #medialiteracy [Video]. TikTok. https://www.tiktok.com/@attemptedsoc/video/7600577414883773726?q=science%20influencer&t=1770339976176 

Tudino, G., & Qin, Y. (2024). A corpus-driven comparative analysis of AI in academic discourse: Investigating ChatGPT-generated academic texts in social sciences. Lingua, 312, 103838. https://doi.org/10.1016/j.lingua.2024.103838 

Introduction 

Generation Z, born between 1997 and 2012, has grown up fully immersed in digital technology. As one of the first generations to be considered “digital natives,” they have developed communication styles shaped by social media and instant messaging apps (Manzoor, Sultan, & Siddique, 2026). These linguistic styles carry over into professional settings as Gen Z enters the workforce, potentially reshaping workplace communication and expectations around professionalism. A greater emphasis on short, efficient communication may lead to an increase in casual linguistic features such as greetings, emojis, slang, and abbreviations, rather than traditional emails characterized by rigidity and formality. For instance, interviews with Gen Z managers emphasize the importance of being “clear, concise, and kind—even if that includes a meme or emoji” rather than writing dense, highly formal emails (Manzoor et al., 2026). Politeness norms are also evolving, influenced by platforms such as TikTok and Instagram (https://www.tiktok.com), which shape trends in tone, humor, and informal expression and may contribute to intergenerational miscommunication (Jones, 2025). These shifts can reinforce misconceptions that Gen Z employees are lazy, overly informal, or unprofessional, a perspective that is frequently debated in professional spaces such as LinkedIn, where users discuss workplace tone and communication norms (https://www.linkedin.com). 

Despite growing research on Gen Z in the workplace (Zahra et al., 2025), there remains a gap in understanding how college-aged individuals apply these digitally influenced communication styles in professional emails and how they perceive professionalism. This study investigates the degree of formality Gen Z uses with workplace superiors, focusing on informal markers such as slang, contractions, emojis, abbreviations, tone, and directness. We hypothesize that Gen Z employees will generally rate informal linguistic features as appropriate and will incorporate them into their email responses, particularly in lower-stakes contexts 

Methods

The study included 18 Gen Z participants between the ages of 18 and 30 who were undergraduate or graduate students with current or prior work experience. Data were collected through an online survey distributed via platforms such as GroupMe and Slack. Participants first rated the perceived professionalism of various linguistic features—including emojis, exclamation points, slang, abbreviations, and casual greetings—using a 5-point Likert scale. Participants then completed three situational prompts requiring them to write mock email responses to a supervisor. These scenarios included requesting time off, responding to criticism regarding time management, and replying to a holiday party invitation. Responses were analyzed for linguistic features such as greetings, closings, tone, contractions, slang, and emoji usage. Drawing on previous research suggesting increased informality in digital communication among Gen Z (Rotich & Mary, 2025), we examined how participants adjusted their language across different contexts. This approach allowed us to assess patterns of code-switching between formal and informal communication depending on situational demand

Results

To better understand these patterns, we first examined participant demographics. A total of 18 participants completed the survey, with ages ranging from 18 to 29. The majority were undergraduate students (66%), followed by individuals who had completed graduate school (16%), were currently in graduate school (5%), held a high school diploma (5%), or held a bachelor’s degree (1%). Approximately 70% of participants were currently employed, and all
reported prior work experience across a range of settings, including corporate (29%), retail or food service (23%), education (18%), nonprofit (12%), healthcare (11%), and childcare (6%).

Figure 1

Number of Participants by Age Range

Note. This bar graph displays the distribution of participants across age groups, with the majority of respondents falling between ages 21 and 24. 

Firgure 2

Distribution of participants by workplace setting.

Note. This pie chart illustrates the variety of work environments represented in the sample, including corporate, retail/food service, education, healthcare, nonprofit, and other sectors. 

Participants showed mixed opinions about what counts as professional communication. Emojis were viewed as highly context-dependent, with 47% rating them as neutral and 41% as somewhat professional. Exclamation points were more positively perceived, with 53% rating them as very professional and 41% as somewhat professional. Casual greetings such as “hi” or “hey” were generally viewed as somewhat professional. In contrast, abbreviations (e.g., “lol,” “btw”) were widely considered unprofessional, with 41% rating them as very unprofessional and 35% as somewhat unprofessional. Slang showed similar patterns, with responses ranging from neutral to very unprofessional. Short messages produced mixed responses, indicating no clear
consensus.

Figure 3

Average perceived professionalism of informal linguistic features.

Note. This figure shows that emojis and exclamation points were rated more positively, while slang and abbreviations were consistently viewed as less professional. 

Analysis of the email responses revealed that linguistic choices varied by context. In high-stakes situations, such as responding to criticism, participants used minimal informal features. In contrast, lower-stakes contexts, such as responding to a holiday party invitation, showed higher use of informal markers. The time-off request scenario reflected a balance between formal and informal language. Overall, these findings suggest that the use of informal linguistic features is context-dependent, with more formal situations discouraging informality and less formal contexts allowing for greater flexibility. 

Conclusion

So what does this actually mean in a real workplace? Our findings suggest that Gen Z employees have a nuanced and context-dependent understanding of professionalism in digital communication. While media portrayals often depict Gen Z as overly informal, our results indicate that participants seem aware of professional expectations and adjust their communication accordingly. More formal situations, such as responding to criticism, prompted more structured and professional language, while lower-stakes contexts allowed for more relaxed and expressive communication. 

Although features such as emojis, exclamation points, and casual greetings were generally viewed as acceptable in moderation, slang and abbreviations were widely considered unprofessional. Interestingly, many participants still incorporated informal features into their emails despite recognizing these boundaries, suggesting a potential gap between perception and practice. Additionally, consistently high self-ratings of professionalism indicate that participants may perceive their communication as more formal than it appears. 

Ultimately, these findings suggest that Gen Z is not abandoning professionalism but is actively redefining it to include more flexible and expressive forms of communication, shaped by digital culture and contextual expectations, an evolution also reflected in broader discussions of language and communication in public-facing platforms and resources such as the Lingthusiasm podcast (https://lingthusiasm.com). In this way, professionalism is not disappearing, it is evolving. Gen Z is not breaking the rules of workplace communication, but rewriting them for a digital age. 

References

Glikson, E., et al. (2024). Emotional leader communication in the digital age: An experimental investigation on the role of emoji. Computers in Human Behavior, 154, 108148. https://doi.org/10.1016/j.chb.2024.108148 

Jones, R. D. (2025). The complexities of impoliteness in digital workspaces: A politeness theory analysis of Gen Z workplace communication (Publication No. 7760) [Doctoral dissertation, Liberty University]. 

Manzoor, A., Sultan, S. A., & Siddique, M. U. (2026). From emails to emojis: How Gen Z is redefining managerial communication through digital media. https://doi.org/10.5281/ZENODO.18345890 

Zahra, Y., Handoyo, S., & Fajrianthi, F. (2025). A comprehensive overview of Generation Z in the workplace: Insights from a scoping review. SA Journal of Industrial Psychology, 51, 1–11. https://doi.org/10.4102/sajip.v51i0.2263 

Introduction & Background

Language is a powerful tool of communication that is constantly negotiating between
power, identity, social norms, and belonging. Not only does the world around us shape how we
communicate, but so do our personal identities and the communities we belong to. Because of
this, our everyday language practices and uses signal the broader social hierarchies and cultural
norms to which we adhere. To better understand this phenomenon, we wanted to look at a
multilingual community that practices language maintenance and code-switching, in the hopes of
finding patterns between language use and social hierarchies. We decided to focus on the
Spanish-speaking community of Los Angeles, where the language has deep historical roots; in
fact Los Angeles County has the largest Spanish-speaking population in the United States (Los
Angeles Almanac, n.d.). Prior research on Spanish language maintenance and shifts in the United
States shows generational patterns where first-generation immigrants tend to maintain the use of
Spanish, while second-generation speakers increasingly shift towards the use of English. This is
especially true for public and professional spaces (Michnowicz et al., 2023).
In this study we hope to answer this question by studying code-switching between
English and Spanish in public and private spaces. Code-switching is not treated here as random
mixing of languages, but as a socially meaningful practice that reflects audience, context,
institutional expectations, and perceived legitimacy. We also consider how heritage and
Indigenous languages are maintained, marginalized, or erased within Spanish-speaking
communities. Drawing on a raciolinguistic perspective (Phuong, 2024), we look at language and
race as co-constructed through dominant listening practices and institutional norms. Going in, we
hypothesize that in communities where multilingualism is actively accepted and supported,
speakers are more likely to maintain and use Spanish and other heritage languages instead of
defaulting to English. This connects to the ways in which social hierarchies are either reinforced
or challenged, which is the central focus behind our research question: How do power relations
and cultural norms shape multilingual practices and contribute to Spanish language maintenance
or shift among Spanish-speaking communities in Los Angeles? Our findings suggest that these
dynamics operate not only through institutional preference for English, but also through internal
community expectations about what forms of Spanish or mixed speech are considered legitimate

Methods

To gather data, we used a mixed-methods approach including surveys, participant
observation, and informal interviews. Our surveys were developed to measure comfort speaking
English and Spanish across different contexts, sources of linguistic pressure, and language
modification through likert-scale questions, multiple-choice responses, and open-ended prompts
to gather both quantitative and qualitative data. For the Spanglish-focused survey, conceptually
related Likert-scale items were also combined into a simple index to capture overall attitudes
toward the legitimacy of Spanglish. Participant observation was conducted through informal
conversations within family and community contexts, paying close attention to code-switching
patterns and language or accent modification and shifts. Semi-structured interviews also allowed
participants to describe moments when they changed their language use due to perceived power
dynamics, safety concerns, or social expectations. This combination of methods allowed us to
analyze multilingual practices from multiple angles, providing data on larger patterns and
backing it up with our observations and inquiries

Results & Data Analysis

After our data collection, we cross-analyzed results from each part of our research. Our
survey responses provide us with overarching patterns on a quantitative level, while our
observations and interviews back up our findings and may help to make sense of these patterns.
Most notably, we observed patterns of Spanish being the primary language used in home and
family spaces, whereas English was predominantly used in school, work, and government
settings (Figure 1). This supports the notion that setting and institutional authority influences
language use and can either support or hinder the use of a non-English language.

Figure 1 – Language Use by Context

Note. Results collected from a checkbox matrix in the study’s survey.

Another notable aspect of our results was the data on Spanish proficiency and judgement
around language use. As shown in Figure 2, survey participants generally rated their Spanish
speaking and listening proficiency higher than their Spanish reading and writing proficiency.
Along with our data on Spanish being used frequently in private settings, these trends suggest
that Spanish is typically learned more through practice than formal education. Furthermore,
Figures 3 and 4 show that people have tended to feel more judged for their Spanish use, perhaps
due to a lack of comfort with Spanish proficiency.

Figure 2 – Language Proficiency

Figure 3 – Accent & Perception: English

Figure 4 – Accent & Perception: Spanish

Along similar lines, we looked a bit further into the use of Spanglish, a linguistic hybrid of Spanish and English together. Survey responses suggest that Spanglish is widely understood as an important linguistic resource, although respondents remain cautious about its use in professional settings (Figure 5). Once again, this demonstrates the difference in linguistic approaches to “professional” settings and official situations, which introduce society’s hierarchical pressures.

Figure 5 – Spanglish

Survey responses suggest that many participants view Spanglish as meaningful in everyday communication, particularly for identity, emotional expression, and belonging, even while remaining cautious about its use in professional settings. The initial survey responses showed strong but context-dependent attitudes toward Spanglish; we developed a second survey to examine how speakers assess its legitimacy, usefulness, and social perception.

To move beyond individual survey responses, we created two simple indices using Likert-scale items. The first, a Spanglish Legitimacy Index, combined five questions measuring whether respondents viewed mixed speech as culturally meaningful, socially useful, legitimate, emotionally expressive, and connected to belonging. Each response was coded on a scale of 1 to 5, with higher scores indicating more positive attitudes toward Spanglish. The average score across responses was 3.66 out of 5, suggesting that respondents generally viewed Spanglish positively.

Figure 6 – Spanglish – Data A

Legitimacy Component	Mean
Cultural Identity	4.00
Social usefulness	3.57
Legitimacy	3.64
Emotional Expression	3.57
Belonging	3.50
Overall Index	3.66

Note. Means calculated from five Likert-scale survey items (1 = strongly disagree, 5 = strongly
agree). Higher scores indicate more positive attitudes toward Spanglish. For interpretation,
mean scores closer to 1 indicate low agreement, scores near 3 indicate mixed or neutral
attitudes, and scores closer to 5 indicate strong agreement. Following this scale, values above
roughly 3.5 suggest generally positive attitudes, while values between 2 and 3.4 indicate more
moderate or mixed responses.

The strongest agreement appeared in the area of cultural identity, suggesting that
respondents understand Spanglish less as random linguistic mixing and more as a meaningful
marker of lived bilingual experience. Slightly lower scores in belonging and usefulness suggest
that while respondents generally value Spanglish, its acceptance remains shaped by context,
especially where social expectations or institutional norms influence language choice.
To examine whether this positive valuation coexists with linguistic pressure, we also
created a second index focused on stigma and normative expectations surrounding language use.
This Spanglish Stigma Index combined items measuring whether speaking Spanglish can make
someone seem less educated, whether proper Spanish is seen as important within the community,
and whether respondents had experienced criticism from Spanish speakers

Figure 7 – Spanglish – Data B

Stigma Component	Mean
Speaking Spanglish can seem less educated	2.86
Proper Spanish matters in the community	3.29
Criticism from Spanish speakers	2.00
Overall Stigma Index	2.72

The overall stigma score of 2.72 falls within the moderate range, suggesting that although
strong stigma was not dominant across responses, respondents still reported noticeable pressure
around language correction and ideas of proper Spanish. In particular, the relatively higher score
for “proper Spanish matters” indicates that ideas of linguistic legitimacy continue to circulate
within the community itself, not only through outside institutions. Taken together, these two
indices show that positive identification with Spanglish coexists with lingering expectations
about when and how mixed speech is socially acceptable.

Discussion & Conclusion

The findings of our study show notable patterns and correlations that support our hypothesis. Overall, we found evidence that English indexes professionality, as it is the preferred language used in more institutional and professional settings. This shows how power hierarchies, particularly those in the United States that show preference to English speakers, maintain influence and control over which language is deemed socially acceptable to use in particular settings. Although English is the official language of the US, and therefore Los Angeles, this evidence still suggests that there is a general lack of support and acceptance of multilingualism.

In the context of our collected data (Fig. 1-4) and associated research, we suggest that a lack of institutional support for multilingualism and the Spanish language denies speakers opportunities to build proficiency, leading them to learn informally in private spaces, often through family and friends. This is perhaps the reason that many speakers feel more judged for their Spanish speaking abilities than English (Fig. 3-4), as they have not been formally taught Spanish as they were with English in school.

At the same time, the Spanglish survey shows that legitimacy is not absolute. Although respondents scored positively overall on the Spanglish Legitimacy Index (3.66), the Spanglish Stigma Index (2.72) indicates that moderate pressure on language norms remains. This suggests that language legitimacy operates unevenly: speakers may personally value Spanglish while still recognizing that certain forms of mixed speech can be judged negatively, especially in contexts where professionalism, education, or ideas of proper Spanish are emphasized. The relatively higher stigma score around “proper Spanish matters” further suggests that these pressures do not come only from institutions, but also circulate within the community itself. In this way,
Spanglish does not simply resist power structures; it also reveals how speakers continuously negotiate them in everyday interaction.

Nevertheless, Spanish remains a very important part of people’s lives, as it can be used as a tool to strengthen family ties, friendships, and community membership. Language use now develops in the context of these multicultural communities, which is where Spanglish enters the discussion as a tool to fuse together identity and perspectives while also reflecting one’s identity and multicultural group membership.

References

Phuong, J., Cioè-Peña, M., & Chinchilla, A. (2024). Raciolinguistics. Oxford Research Encyclopedia of Linguistics. Oxford University Press. https://doi.org/10.1093/acrefore/9780199384655.013.1001

Michnowicz, J., Trawick, S., & Ronquest, R. (2023). Spanish language maintenance and shift in a newly-forming community in the Southeastern United States: Insights from a large-class survey: Hispanic Studies Review 7(2). https://hispanicstudiesreview.cofc.edu/article/77601-spanish-language-maintenance-and-shift-in-a-newly-forming-community-in-the-southeastern-united-states-insights-from-a-large-class-survey Links to an external site.

Los Angeles Almanac.(n.d.). The Spanish language in Los Angeles County, California. https://www.laalmanac.com/population/po48s.php

Koskinen, Jeanette, and Josefine Karlsson. “Teachers as Linguistic Role Models: Language Teaching in Multilingual ECEC Settings.” Journal of Early Childhood Education Research, vol. 14, no. 2, 2025, pp. 140–68, https://doi.org/10.58955/jecer.147607.

Cenoz, J. (2013). Defining Multilingualism. Annual Review of Applied Linguistics, 33(Mar), 3–18

Appendix

Interviewer: Do you feel pressure to speak English in certain public spaces?Participant A:“Yes, especially at work. Even if everyone understands Spanish, English feels more official. Like it makes you look more educated.”Interviewer: What about at home?Participant A:“At home it’s the opposite. If I spoke only English with my parents it would feel distant.”

Observation Context: Informal family gathering. Conversation shifts fluidly between Spanish and English. Spanish is used for storytelling and emotional expression. English appears during references to work or academic topics. No visible hesitation in switching.Observation Context: Workplace interactionSpanish-speaking employees initially converse in Spanish. When a supervisor enters, conversation shifts entirely to English. The tone becomes more formal. Code-switching decreases.

Sample Survey Questions

Research Question: LOL vs 😂: How Digital Laughter Varies Across Generations

Introduction and Background            

For this project, the target population will be Generation Z and Generation Alpha. Generation Z refers to those born in 1997 up until those born in 2012. Generation Alpha refers to those born in 2010 up until those born in 2024. With digital communication being one of the main sources of communication in today’s world, we want to explore how the two most recent generations, more specifically the younger generations, have become linguistic innovators. In these more recent generations, it has become evident that people now create their own rules for punctuation and have normalized not using punctuation (Guo, 2016). Both Generation Z and Generation Alpha have grown up using technology. From smartphones to social media to messaging platforms, both generations have been surrounded by technology as a main source of communication. In typical face-to-face communication, people physically show their emotions, whether they are happy, sad, excited, shocked, angry, humorous, etc. However, in today’s digital world, those non-verbal cues like facial expressions and vocal intonation are replaced by the use of emojis and expressions of amusement. The specific expressions we are going to focus on for this project are “LOL, LMAO, and HAHA,” and when they are being used by Gen Z and Gen Alpha, as well as certain emojis that pertain to humor. It is made clear that age is something that significantly impacts how emojis are classified (Chen et al., 2024). It is well established that textese are commonly used (Sánchez-Moya & Cruz-Moya, 2015). Both generations tend to use these phrases digitally quite often. “LOL” is an acronym that means laugh out loud, and over time, it has been used as a tone marker instead of an actual sign of laughter. “LMAO” is a more bold and exaggerated phrase to signal laughter, and “HAHA” is also used to express genuine laughter. Understanding the reasoning behind these linguistic patterns will allow for more expansive knowledge on how digital communication norms evolve and continue to grow amongst the new generations and today’s youth.

Methods

Our approach was to collect data using our two population groups. These participants were chosen due to their generational ages and the majority of individuals had relationships to the researchers. These relationships consisted of group members and included siblings, roommates, friends, classmates and cousins.

Next, the materials used throughout our research were observable data through screenshots of text messages and google form surveys to collect individual data. We first collected the observable data using real life conversations within text messages and organized these into the two generational groups. After collecting observable data we created google form surveys to either discredit or prove our origin hypothesis. The survey used the same questions for both generations and included 10 responses from Gen Z and 10 responses from Gen A participants. This survey began by asking those engaging in the study to indicate whether they are Gen Z or Gen A. Then, the succeeding question followed with a “Select All That Apply” to indicate which styles (i.e. lol/LOL, haha/HAHA, lmao/LMAO, 😭, 😂, 💀) of digital laughter they use. Additionally, the next questions after those included Likert scales ranging from (1) Not at All to,  (5) Frequently. This scale determined the likelihood and frequency of each form of digital laughter and allowed us to measure the different forms of usage between each generation. The survey questions are specific to ensure detailed conclusions of responses, which changes in polarity to see visible opposing viewpoints. Although, due to using the survey method, the participants must have personal accountability to respond truthfully. All responses collected were anonymous and included all participants to agree on responses being used publicly.

Furthermore, the data collected within this methodological procedure was coded using all participants’ responses to understand the opposition among generations. Using the survey responses we divided each individual reply into Gen Z and Gen A categories. We then analyzed each form, marking down each response from all 13 questions. This is how we gathered the differences between frequency and style of digital laughter used in online communication styles between Gen Z and Gen A. This procedure allowed us to determine statistical data in which we could affirm or negate the hypothesis from our observable data.

Results and Analysis

Through the collection of our data, we were able to confirm details within our hypothesis as well as gather new information that supported our research study. Our results suggested that while both generations profusely engage in online laughter, there is a difference in how they use it and in what forms. For example, results from our survey collection indicated higher use of overall online laughter particularly verbal laughter amongst Gen Z with phrases such as “lol/LOL” and “lmao/LMAO” receiving 70-80% usage compared to that of Gen A’s (55% and 11%). Gen A on the other hand relied on emoji usage more so than Gen Z. However as per survey data, Gen A participants were less likely to use digital laughter than their counterparts. These results were portrayed through our bar graph which compared digital laughter use among the generations with Gen Z represented in teal color and Gen A through blue. When comparing verbal laughter and emoji usage, our graph depicted patterns of Gen Z participants selecting verbal responses with ranging levels of 2-4 while Gen A participants selected fewer verbal responses and drifted to emoji usage at higher levels. As stated previously, these results aided in identifying patterns between the generations and noting the differences in expression through online laughter.

Based on the results, we see that while there are some differences between the two generations, there are no big differences. Usually when comparing 2 different generations, there are clear and distinct differences, often big ones. However, we found that the differences are hardly any and relatively small. The small differences can show how similar and closely related these 2 generations are in regards to digital communication and emoji usage. The gap between generations is not large, they have some nuances but it doesn’t stop them from effectively communicating with each other. Our findings show that both Gen Z and Gen Alpha frequently use digital laughter, but slightly differ in how and with what tone they express it. Emojis allow us to speak in ‘gestures’ through digital platforms and let conversation flow more freely (McCulloch, 2019). It is almost as if texting is the new speaking in-person in today’s day and age. While texting using digital laughter, in a study done on Whatsapp, researchers found that this turn-taking was similar to face-to-face conversations (Petitjean & Morel, 2017).

Discussion and Conclusion

Based on the results, we see that while there are some differences between the two generations, there are no big differences. Usually when comparing 2 different generations, there are clear and distinct differences, often big ones. However, we found that the differences are hardly any and relatively small. The small differences can show how similar and closely related these 2 generations are in regards to digital communication and emoji usage. The gap between generations is not large, they have some nuances but it doesn’t stop them from effectively communicating with each other. Our findings show that both Gen Z and Gen Alpha frequently use digital laughter, but slightly differ in how and with what tone they express it. Emojis allow us to speak in ‘gestures’ through digital platforms and let conversation flow more freely (McCulloch, 2019). It is almost as if texting is the new speaking in-person in today’s day and age. While texting using digital laughter, in a study done on WhatsApp, researchers found that this turn-taking was similar to face-to-face conversations (Petitjean & Morel, 2017).

As Gen Z college students ourselves, we are aware that the majority of Gen Z had a childhood without texting, but as we grew older, we started to text more using emojis and digital laughter as those evolved. While Gen Alpha grew up with texting, we wanted to explore if that dynamic made a difference in the use of digital laughter between the two generations. Early Gen Z are digital natives but vividly remember analog life. They’re the last generation who remembers what it was like to have a flip phone as their first device, use physical CDs or DVDs, write handwritten letters or notes, and live without constant access to everything online. Yet, they adapted to technology so quickly that they can navigate both analog and digital worlds fluidly. Gen Alpha however, cannot relate to that since emojis and digital laughter have been around since the beginning of that generation. For example, the “tears of joy” emoji, or the first laughing emoji was created in 2010, which is the beginning of Gen Alpha. Digital laughter amongst both generations is a crucial part of online communication and a way of expression.

References:

Chen, Y., Yang, X., Howman, H., & Filik, R. (2024). Individual differences in emoji comprehension: Gender, age, and culture. PLOS ONE. https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0297379

Guo, J. (2016). Stop. Using. Periods. Period. – The Washington Post. The Washington Post. https://www.washingtonpost.com/news/wonk/wp/2016/06/13/stop-using-periods-period-2

McCulloch, G. (2019, June 1). Because the internet: Understanding the new rules of language. Explorations in Media Ecology. https://doi.org/10.1386/eme_00039_5

Petitjean, C., & Morel, E. (2017, January 25). “hahaha”: Laughter as a resource to manage WhatsApp conversations. Journal of Pragmatics. https://www.sciencedirect.com/science/article/pii/S0378216616302594

Sánchez-Moya, A., & Cruz-Moya , O. (2015, April 21). WhatsApp, Textese, and moral panics: Discourse features and habits across two generations. Procedia – Social and Behavioral Sciences. https://www.sciencedirect.com/science/article/pii/S1877042815013786

Introduction and Background

Texting has become a primary mode of interaction, and with it, a new kind of nonverbal language has emerged. As digital communication becomes more widely used to communicate, the rules for how one should interpret a text aren’t always agreed upon. Their interpretations vary due to our age and experience within our generational environments. What feels natural and obvious to one generation can feel informal, confusing, or new to another.

This study aims to investigate how two generations, Gen X and Gen Z, navigate digital body language. Our study begins by introducing digital body language (DBL), the way people subtly and non-verbally communicate and express themselves through their use of capitalization, punctuation, emojis, slang, acronyms, response times, etc., in constructing online messages (Irshad, 2024). Followed by an overview of our research methods and implementation. Then we present the key findings from the participants’ responses, highlighting generational differences in interpretation, tone, responses, and emoji usage. Finally, we review the broader implications of these different generations and discuss their ability to adapt when navigating unfamiliar digital cues and how their responses may be shaped by varying levels of cultural immersion in the digital age. 

As texting has become a dominant form of communication, people have developed new ways to express tone and emotion without speaking. These include punctuation, emojis, and message interpretations, which researchers often call digital body language. While these features help fill in the gaps left by the absence of facial expressions and vocal tone, their meaning can vary depending on who is reading them.

Prior studies have shown that younger generations tend to use and interpret these digital cues differently from older ones. For example, Gen Z, who grew up immersed in texting and social media, often assigns emotional weight or social meaning to features like lowercase typing or a final period. The New York Post report noted that, to young people, “using a period in messaging now looks rather emphatic, and can come across as if you’re quite cross or annoyed” (Frishberg, 2020). For example, Gen Z, who grew up immersed in texting and social media, often assigns emotional weight or social meaning to features like lowercase typing or a final period. In contrast, Gen X may interpret the same features through a more literal lens, viewing them as grammatical or functional rather than expressive. Binghamton University psychology research found that texts ending in periods were perceived as less sincere than those without punctuation, suggesting that punctuation alone can change emotional tone (Klin, 2016).

Despite growing research in online communication and generational differences, there is still limited understanding of how digital body language is interpreted across generations in casual text exchanges. Our study focuses on this gap by comparing how Gen Z and Gen X understand and use key digital features in message-based conversations. We aim to uncover whether the same text message is read differently depending on the generation of the reader, and what this might reveal about changing norms in digital communication.

Figure 1

Generational Differences in Emoji Use and Interpretation

TikTok – Generational Emoji Usage

Note. A viral TikTok humorously captures the difference between generational interpretations of emojis. The creator of the video explains, “we really gotta teach our parents how to properly use emojis…” then shows the text he received, which said “your uncle Mark died [skull emoji]”. Gen Z often uses the skull emoji to express exaggerated reactions, humor, or sarcasm, unlike Gen X, which interprets this emoji as literal death, which contributed to the message sounding comical and inappropriate.                 

Figure 2

Generational Differences in Texting

YouTube Video – Texting Across Generations

Note. A snippet from a podcast episode discusses how our digital interactions are shaped by our relationships with others. One of the speakers talks about how the way she positions her digital body language depends on the person she’s texting, saying that “different people bring out different texting sides of me” (The Council, 2025). She then goes on to talk about how this switch-up is especially prevalent when she is texting members of older generations, such as her father. When messaging her father, she’s observed that their text conversations are based entirely on message content and practicality, and there’s less of an emphasis on tone and nuances.

Methods

Data was gathered from ten participants, five members of Generation X and five members of Generation Z, through semi-structured interviews. Each interview consisted of the same exact format, but was semi-structured in the way that the design encouraged follow-up questions and elaboration from interviewees. The interviews were divided into four parts: (1) demographic and technology profile, (2) message-interpretation task, (3) punctuation and capitalization, and (4) emoji-choice scenario. The first section collected basic background information, such as age, gender, and technology usage habits. The second part presented five different text messages, written by us. Each message contained one or more features of digital body language—punctuation marks, capitalization or lack thereof, emojis, and acronyms. We showed each participant these messages, one by one, and asked them what tone they perceived and how they would respond. The third exercise was also made up of messages we designed, but it focused on only punctuation and capitalization features, such as capitalizing or not capitalizing the first word of the message, capitalizing the entire message, as well as using a period, exclamation point, or no punctuation at all. It also featured three messages with the same exact word content, but two different versions of each message: Version A and Version B. What set these versions apart were their differing levels and use of punctuation and capitalization. After presenting these two different versions, we then had participants choose which version they think is friendlier and explain why. In the final section, participants were presented with eight different emojis to choose from and asked to choose which two they’d use to respond to a message from a friend announcing a new job. Once interviewees chose their top emojis, we asked them two follow-up questions, which were why they picked those emojis and if their choices would change if the message had come from an acquaintance rather than a friend. Through these interviews, we analyzed how members of these different generations interpreted and expressed various online non-verbal cues, also known as components of digital body language. We sought to identify generational differences and patterns in how each generation processed these features.

Results and Analysis

Based on what we have collected, we have obtained results that can help us make inferences out of the differences between Gen X and Gen Z. We found most importantly that in relation to punctuation and formatting, a period (e.g., “Okay.”) is interpreted as annoyance, finality, and/or passive aggression among our Gen Z interviewees. This follows our literature base where, according to Teresa Apgar, “research suggests that younger individuals interpret text-final periods to be more negative in tone, while older individuals interpret it to be neutral” (Apgar, 2022, 1). When it came to tone shift and identification, we found that Gen Z had a strong sensitivity to changes in tone, particularly when familiar contacts shift from informal to formal texting styles that are reflected in the punctuation and capitalization. Another piece of research literature that helps us understand passive-aggressivity mentioned previously is the situation where both subject Gen Z’ers are observed: “Lisa evaluates Nelly’s [non-punctuation lowercase] reaction as inappropriate by repeating her utterance and adding an iterated question mark” (Busch, 2021, 38). Conversely, lowercase messages without periods were deemed more so as friendly and casual among Gen X interviewees. Now, when it comes to emoji use and interpretation, we found that emoji choice changes depending on the relationship for Gen Z (e.g., [flame emoji] is for close friends). This relationship-dependent emoji use selection was not as prevalent in Gen X responses. We theorize that this lack of variety in emoji usage was probably due to Gen X’s simple lack of exposure time to the emoji features. See Figure 3 below.

Figure 3

Digital Communication Cue Interpretation: Gen Z vs. Gen X

Note. This chart summarizes/simplifies our results as a whole according to relevant categories (extreme left).

Discussion and Conclusion

Our exploration into generational interpretations of digital textual communication demonstrates a divide in how meaning is constructed and perceived across age groups. Through interviews with members of both Generation X and Generation Z, we observed that the tools of modern text-based communication carry different meanings depending on one’s digital fluency and cultural context.

Within Generation Z, we noticed there to be a deeper sensitivity to the emotional and social undertones of simple texting features. Even something as minute as a period at the end of a sentence could indicate a different tone or even a conflict. Generation Z interpreted texts figuratively and consistently attempted to read between the lines.

Contrastingly, Generation X  looked at the texts in a more literal and formal light. Punctuation was used for the purpose of grammar, and emojis were viewed straightforwardly with little subtext. Some members were aware of the subtext, but did not spot it as consistently as their Gen Z counterparts.

A key insight of our study is that, while members of both generations utilize and recognize non-verbal cues in text, Gen Z appears to have developed a more nuanced form of digital literacy. Their fluency allows them to read undertones that older generations would not as easily detect, which may allow them to engage in complex, layered conversations entirely through digital platforms, where meaning is often conveyed as much by how something is said as by what is said.

As digital communication keeps evolving, the language and meaning embedded within it follow. Our findings suggest that generational gaps in digital interpretation are not just a result of age, but additionally, cultural immersion. Many members of Generation Z grew up using computers, tablets, and phones, where communication was quite text-heavy and rich with emoji use. Generation X was not introduced to the same kind of communication until their adult lives; they are perfectly capable of adapting, but the trend for this group is to interpret digital language through a more traditional, literal lens.

References

Apgar, C. T. (2022). Wait wdym?: Examining the (mis)perception of emotional valence in text messaging across generations (B.Phil. thesis, University of Pittsburgh). University of Pittsburgh.

Busch, F. (2021). The interactional principle in digital punctuation. Discourse, Context & Media, 40, 100481. https://doi.org/10.1016/j.dcm.2021.100481

Danger. [@natedanger]. (2021, April 2). Rip uncle mark #family #emoji #fyp [Video]. TikTok. https://www.tiktok.com/t/ZP8MEvPnM

Frishberg, H. (2020). Young people don’t trust anyone who uses this punctuation mark. (2020, August 24). New York Post. https://nypost.com/2020/08/24/young-people-dont-trust-anyone-who-use-this-punctuation-mark/

Irshad, S. (2024). Deciphering digital body language and the Gen-Z in new normal. Creative Saplings 2(10), 31-41. https://creativesaplings.in/index.php/1/article/view/498

Klin, C. (2016, June 12). Study: Punctuation in text messages helps replace cues found in face-to-face conversations. Binghamton University News. https://www.binghamton.edu/news/story/873/study-punctuation-in-text-messages-helps-replace-cues-found-in-face-to-face

The Council. (2025, January 31). Texting across generations: The surprising differences [Video]. YouTube. https://www.youtube.com/watch?v=JcC5_VWPf4U

Introduction and Background

Communication serves as a powerful tool to observe and interpret hidden messages. In the workplace, communication depending on various parts of one’s identity may affect roles, actions, or speaking styles in professional settings; specifically gender and level of experience influence how individuals speak and are addressed. Discourse plays a large role in language and gender studies “because many masculine and feminine aspects of speech emerge during communication” (Kizi, 2024). Social hierarchies and biases can be shown through something as simple as a different tone of voice or body movement. Our research dives into these different forms of communication by gender and level of experience of the employee being addressed.

Before conducting our own research, we searched for information that could be beneficial for us to evaluate to help make conclusions. Past research showed that women and men often use different communication styles; men use report talk, which is assertive and goal-oriented, while women use rapport talk, which places importance on connection and collaboration (Mohindra and Azhar, 2012). Relating back to the workplace, these differences can lead to how workers are valued and judged in professional settings. For example, rapport talk, typically used by women, is seen as less skilled than report talk, often used by men. Additionally, communication that stereotypically aligns with feminine traits is often overlooked in performance evaluations and leadership assessments (Chai, 2022). While we were able to find plenty of research examining communication by gender in the workplace, we were unable to find research that studied age and level of experience that influence communication in the workplace. We were curious to examine the intersection between experience and gender in the workplace. Do older, more experienced women get spoken to with more respect? Do newer female employees experience more condescending tones than their male counterparts? These are questions we were hoping to answer in our own research methods.

Methods

When conducting this study, we first formulated our hypothesis: “How do both gender and professional experience influence tone, word choice, and body language used by supervisors when addressing employees in the workplace?” We wanted to come to a conclusion regarding communication for those of different genders and different positions (hierarchy-wise) in workplaces. Our method consisted of conducting a poll via Google Form, asking our respondents the same set of occupation-based questions. Our questions began with basic intro topics: age, gender, and career experience. We then dove into more personal subjects, creating a list of yes or no questions surrounding communication within the workplace. The questions focused on how each participant is treated and addressed based on their gender. We chose to make each question very straightforward (not open-ended) to avoid any biases in the study. We chose to send this survey to four people each, two of each gender. We wanted to have an equal number of males and females in the study to make our outcome as accurate and honest as possible. We chose participants of all different ages and employment levels. Some were interns, some were in the service industry, some worked high-paying corporate jobs, and some even worked for themselves. The variation amongst every participant provided us with the most transparent results. By focusing on all different backgrounds and levels of experience, we could make a consensus about gender and many different workplaces in 21st-century America. Although our questions required a yes or no response, we focused our topics around rapport and report, displaying differences amongst age, sex, and gender.

Results and Analysis

When our participants were asked if they notice differences in communication styles between their male and female bosses, 64.3% of participants replied “YES,” while 35.7% replied “NO.” One of our participants even shared that their female bosses tend to be more sincere and considerate, while their male bosses take a condescending approach in their workplace. (Johnson, 2017) This manifests itself in the specific tone used by one’s boss. We chose to ask questions about bosses of both genders to come to a consensus with report versus rapport talk. Report and rapport contribute to how each gender takes on an authoritative position, especially in an intense work environment. The results in this pie chart were supported by one of our participants, a young female intern. At the end of our survey, she wrote, “I feel like I get spoken to too harshly by my male bosses and that they give the guys that I work with much more leeway.”

Pie chart displays responses of different experiences between bosses of each gender

In addition to communication between employees and their bosses, we also factored in age to our questionnaire (as stated above). In gender-based studies, age often gets overlooked. Incorporating age as a question in our Google Form allowed us to connect the outcome to our predominantly gender-focused study. Age and gender are without a doubt connected, especially when it comes to male and female interactions on a professional level. When asking about age, 92.9% of our participants said that their age has affected their communication at work. That is almost our entire population, leaving out 7.1%. Age has a direct correlation with work experience, so it is bound to impact communication, how one is addressed by both their peers and authoritative figures, and even how they are perceived by others.

Pie chart displays correlation between age and communication in the workplaces

Younger employees are more likely to be recipients of condescending or belittling behavior. This connects to realistic factors such as lack of experience or deeper ones such as gender. Whatever the motives may be, it is inevitable that age has a direct connection to how one communicates and is communicated with in their workplace.

Discussion and Conclusion

Based on the results of our research, we found three main patterns in communication in the workplace between males and females. The first main finding is same-gender communication leads to  relaxed and informal conversation. Our evidence illustrates how females engage in rapport talk over text and this is consistent with our survey findings because about 64.3% of our respondents reported differences in communication styles between male and female bosses. In an interview, we found that female bosses were perceived as less condescending and more considerate, male bosses were described as “more self-centered.” The second main finding is that Supervisors use more formal and respectful language when addressing experienced employees. We noticed patterns of tone shifts within text conversations. This aligns with our literature review where experience and age shapes the formality in the workplace, and a polite tone may emerge toward more seasoned women. This also connects with our survey findings because 53.8% rated a 4 or 5 (on a 5-point scale) in agreement that they were addressed differently based on age or experience. The third and final theme is long-term experienced employees are spoken to with continued respect, but less formality. We found that texts between male bosses and experienced male employees are more relaxed. This aligns with Holmes and Marra (2004), relational practice evolves over time and becomes less formal with workplace bonds, and Mohindra & Azhar (2012), men adopt direct talk (report) once relationship is established. This connects to our survey results because 92.9% said their age/experience affected communication. Qualitative responses such as “I tend to feel less comfortable with male bosses” reflect same-gender or familiar dynamics. Ultimately, with our research we focused on the differences of language, tone, and communication between men and women in the workforce. Our research highlights gender roles through a lens of language. We aimed to examine the differences in language use amongst themselves, their bosses, clients, colleagues, and especially how they are addressed by their peers. We emphasized tone, word choice, and body language as a whole. Our research question was: Are women addressed with different tones, word choices, and body language than men in the workplace? We hypothesized that gender would influence workplace communication and that women are more likely to be spoken to with different linguistic and behavioral communication when compared to their male counterparts. Our hypotheses were found to be all true as our survey results demonstrated same gender communication leading to more relaxed and information conversations, supervisors being more formal with older more experienced employees, and finally, experienced employees having less formal but still respectful conversations. Our findings imply that there is only a small amount of discrimination in the workplace through communication styles or behaviors among colleagues or bosses based on one’s gender or experience. Further, when one stays longer in one job, they attain more respect and are more lenient with their formality/conversation styles. Gender can cause more formal, serious tones and closed off body language between male bosses and female workers. This is because of gender perceptions of female competence and ability to get work done. Women have to work harder to prove their capabilities and this causes women to engage in rapport talk whereas men engage in report talk. Furthermore, our findings are important because it illustrates why men and women generally use different communication styles and how it can boost their status or job performance.

References

Mohindra, V., & Azhar, S. (2012). Gender Communication: A Comparative Analysis of Communicational Approaches of Men and Women at Workplaces. IOSR Journal of Humanities and Social Science, 2, 18-27.

Chai, Y. (2022). Implicit gender-biased speeches in workplace: Embedded stereotypes and effects on women’s Career Development.

Johnson, Stefanie K. “What the Science Actually Says about Gender Gaps in the Workplace.” Harvard Business Review, 17 Aug. 2017, br.org/2017/08/what-the-science-actually-says-about-gender-gaps-in-the-workplace. Accessed 05 June 2025.

Holmes, J., & Marra, M. (2004). Relational practice in the workplace: Women’s talk or gendered discourse? Language in Society, 33(3), 377–398. https://doi.org/10.1017/S0047404504043039

Ergasheva Nozima Khasan Kizi (2024). GENDER DIFFERENCES IN COMMUNICATION IN THE WORKPLACE. Eurasian Journal of Social Sciences, Philosophy and Culture, 4 (6-1), 171-175. doi: 10.5281/zenodo.12176621