Sociolinguistics

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

Introduction and Background

Across digital spaces, content creators strive to present themselves effectively in various contexts. Over the past decade, the rise of young female vloggers has transformed YouTube from a video-sharing platform into a complex stage for influencer culture. These creators document life. Yet, they also navigate the pressures of visibility and social norms in a highly curated world. As the YouTuber phenomenon continues to grow, the importance of understanding how people perform their online identity is ever essential.

Previous research by Abdul Razak (2025) has focused on influencers’ linguistic patterns, such as the use of the word “like.” Other studies have concentrated on influencer actions (e.g., taking selfies) (Adidin, 2016). However, there is a limited understanding of how gestures overall may change based on context for female-identifying content creators. Drawing on Goffman’s (1959) concept of impression management, this project considers how vloggers may act as performers on a digital stage. Abidin’s (2016) theory of subversive frivolity reframes seemingly lighthearted content as sites of resistance, where femininity becomes a tool for navigating digital labor. Hence, this existing literature further legitimizes the inherent merits of our research focused on shifts across content by this group of young, female YouTubers who are often dismissed.

This study examines how undergraduate female YouTubers utilize nonverbal cues in their casual versus serious videos. This examination seeks to contradict the perception of this group as one-dimensional and hypothesizes that our sample changes their gestures to fit the situation — more expressiveness (a higher amount of hand gestures and more relaxed posture, head movements, and hand openness) in casual videos and less in serious ones.

Methods

We began our study by observing five female YouTubers based on their popularity, as we were interested in analyzing videos with high admiration. We noted creators who had verified statuses, a strong following, and a high number of views. We focused mainly on those with over ten thousand subscribers, which then led to a high viewer count on the videos we chose. Our selection included twenty videos total, with two casual and two serious videos per creator. This came out to four videos for each of the five creators. Each one was determined as casual if it involved low social or personal stakes, like “a day in the life,” while serious videos included high social or academic stakes, such as career planning. We randomly selected a five-minute clip to observe from each one with an online number generator (numbergenerator.org), to remove any sort of bias. We recorded data when the YouTuber had their face visible on the screen and spoke to the audience. With each clip, we examined multiple gesture categories due to their associations with expressiveness. These gestures were adaptors, illustrators, emblems, posture, hand openness, and head movements.

We then coded each clip by counting the raw numbers of illustrators, adaptors, and emblems we observed per clip. Illustrators are gestures that send a message, like pointing or placing a hand on your chest, as shown in Figure 1.

Figure 1: Example of Illustrator from Lihn Troung’s “A week in my life: college finals & christmas in the city // vlog 007”

Adaptors, on the other hand, involve self-touching behaviors like scratching or rubbing and are typically unconscious responses to adapt to one’s environment (Kelmaganbetova et al., 2023). Figure 2 shows an example of an adaptor from Lihn Troung’s videos where she tucks her hair behind her ear.

Figure 2: Example of Adaptor from Lihn Troung’s “A week in my life: college finals & christmas in the city // vlog 007”

Emblems are substitutes for words or phrases in communication, like the peace sign shown in Figure 3.

Figure 3: Example of Emblem from Lihn Troung’s “A week in my life: college finals & christmas in the city // vlog 007”

Our next step was to further observe and calculate each video’s expressiveness. We did this in terms of the creators’ posture, hand openness, and head movements throughout the videos. To code this step, we utilized a Likert scale to determine the levels of each gesture displayed by the creator. For instance, a video with relaxed posture would have a rating of 1 on the Likert scale, while a rating of 5 would indicate formal levels of posture throughout the video. The same was for hand openness where a 1 meant closed hand positions, and a 5 meant open. High levels of head movement received a rating of 5, while still head movements received a 1. We performed interrater testing as well, in order to ensure overall consistent results. This testing measured consistency by having more than one group member collect the data.

Results and Analysis

The data set partially lined up with our prediction. Our group’s hypothesis was that young women in undergraduate programs would have a significant difference in gestures between serious and casual content. Our data demonstrated some differences between serious and casual contents’ data. However, there seemed to be more variance between the person that had uploaded the videos themselves versus their actual content type. Something we noticed was that postures would be more “correct” or upright in serious videos in general. Meanwhile, casual videos often had slouchier or relaxed posture. The frames were another factor that typically depended on the type of video that was being seen. For example, shoulders up was the frame that was seen in serious videos. On the other hand, videos that were more casual typically had a less consistent frame. Throughout the videos there was also a difference between different creators. Lihn Truong was the only creator that we viewed that fit the prediction that nine or more illustrators would be visible in casual content. Helaine Zhao and Studyquill had less gestures when filming serious content. Some of the creators kept many of their video styles pretty consistently. Mikayla Mags would be an example of a creator that had high illustrators across video types. Mags also kept a similar posture throughout her videos. Other things that we noticed among videos were that some creators had lower gestures on the Likert scale despite a difference in content type. Lillian Zhang kept a formal style of video content and personality throughout. The patterns observed demonstrate how tone and individual creators overall have more variety rather than their content type. It can be connected to sociological themes such as gender and women trying to be perceived as likable by other people due to societal expectations to be kind and nurturing. This can potentially come across differently depending on the content creator and what they perceive to be according to standard. It is also important to note that this may be a subconscious decision to do so.

Figure 4 shows the gesture counts calculated for Lihn Troung’s videos, along with the Likert scale data for each one. As shown in her casual holiday vlog, she used 10 illustrators, 5 adaptors, and 4 emblems. We can see that her serious content showed more restrained posture, fewer gestures, and closed body language. For more detailed counts and results, see the data table linked at the bottom of this post.

Figure 4: Results from Lihn Troung’s Videos (Raw Counts and Likert Scale)

Video Title	YouTuber	Vlog type	Illustrators	Adaptors	Emblems	Posture	Hand Openness	Head Movements
A week in my life: college finals & christmas in the city // vlog 007	Lihn Troung	Casual	10	5	4	5	5	5
another productive day in my life studying, coffee omakase, dance practice, & senior year memories	Lihn Troung	Casual	8	1	3	4	4	4
why you need hobbies in 2024 // rediscovering my hobbies as a burned out college student	Lihn Troung	Serious	6	1	3	2	4	5
study with me for college finals (pomodoro method)	Lihn Troung	Serious	6	4	7	2	2	1

Regarding other overall trends, illustrators were the most frequently counted gesture. Casual vlogs showed higher amounts of adaptors and emblems; however illustrators actually appeared more frequently in serious videos. Yet, serious vlogs showed fewer hand gestures as depicted in Figure 5.

Figure 5: Relationship between Gesture Counts of Casual vs. Serious Videos

X-axis: Nonverbal Gesture

Y-axis: Number of Counts

Examining the data from the Likert scale included in Figure 6, casual videos had an average score of 4.4 for head movements while serious videos scored an average of 4.8, depicted variation in relaxed and expressive behavior. However, hand openness remained consistent across topics, contradicting part of our original hypothesis which predicted that hand openness would be more prevalent in casual content.

Figure 6: Average Ratings of Expressiveness using Likert Scale (1-5)

X-axis: Expressive Gesture

Y-axis: Rating

Thus, while variation occurred between YouTubers, with some like Linh Troung adhering to our hypothesis closely while others like Makayla Mags presented some contrasting data, overall, a distinction in gestures between causal versus serious content is visible.

Discussion and Conclusion

Overall, YouTubers in casual vlogs displayed more expressive behaviors — more adaptors and emblems, relaxed posture, and head movements. In contrast, serious vlogs tended to feature more restrained gestures yet a higher number of illustrators. Although these patterns largely supported our hypothesis and the results from previous literature, individual variation between vloggers and the counts for illustrators suggests the benefits of a further study.

Our sample size of five female undergraduate YouTubers is one limitation of our study. While this small group allowed for detailed coding, it curbs the generalizability of our results. Furthermore, although the structured coding scheme and interrater testing helped mitigate bias, gesture analysis inherently involves some degree of interpretation. Distinguishing between an illustrator and an adaptor can be context-dependent. Without direct input from the creators themselves, interpretations largely remain speculative — especially regarding intentionality. It is also uncertain how gender specifically shapes these behaviors. Future research could compare how gestures differ between a sample of male versus female YouTubers.

Although additional research may help us derive more concrete overall conclusions about our population, our study offers several benefits to the study of interpersonal communication and societal understanding of internet culture. Our research challenges stereotypes about female influencers by showcasing their context-sensitive nonverbal use. The shift in physical behavior depending on the topic can suggest acute awareness of audience expectations. These patterns contribute to our broader understanding of impression management as gestures take on a layered meaning. The openness adopted in casual vlogs reflects a negotiation of credibility. In serious videos, reducing gesturing and maintaining an upright posture aligns with traditional markers of authority, while in casual contexts, animated movement may serve to build rapport and relatability (Smith, 2017). Gestures become a coded method of exploring platform visibility, societal norms, and professional aspirations.

The findings point to a broader takeaway — nonverbal communication is a vital aspect of digital self-presentation. Although these gestures may be subtle, they wield significant implications for how we understand identity, labor, and gender in the age of influencers.

EXTENDED DATA TABLE + COUNTS

• https://docs.google.com/spreadsheets/d/1RnSxkMVnGdnex0hzXd5Kp_PWCNb36AltPVLHQpakhfs/edit?usp=sharing

RECOMMENDED READING/VIEWING (RELEVANT INFO)

• https://youtu.be/ZzEOs9bVpZQ?si=g0jPMMVomBFOFCV6
• https://languagedlife.ucla.edu/sociolinguistics/the-linguistic-switcheroo-navigating-style-shifts-in-college-discourse/
• https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2025.1568341/full
• https://www.talkabouttalk.com/gender-differences-in-communication-ep-141/

REFERENCES

Abdul Razak, N. (2025). The use of slang by Gen Z female influencers on Instagram and Twitter (X). International Journal of Research and Innovation in Social Science, 9(4), 1910–1917. https://rsisinternational.org/journals/ijriss/articles/the-use-of-slang-by-gen-z-female-influencers-on-instagram-and-twitter-x/

Abidin, C. (2016). “Aren’t these just young, rich women doing vain things online?”: Influencer selfies as subversive frivolity. Social Media + Society, 2(2), 1–17. https://doi.org/10.1177/2056305116641342

Goffman, E. (1959). The presentation of self in everyday life. Anchor Books. Retrieved from https://archive.org/details/presentationofs00goff

Kelmaganbetova, A., Mazhitayeva, S., Ayazbayeva, B., Khamzina, G., Ramazanova, Z., Rahymberlina, S., & Kadyrov, Z. (2023). The role of gestures in communication. Theory and Practice in Language Studies, 13(10), 2506–2513. https://doi.org/10.17507/tpls.1310.09

Number Generator. (n.d.). NumberGenerator.org. Retrieved June 10, 2025, from https://numbergenerator.org (https://numbergenerator.org/)

Smith, H. J., & Neff, M. (2017). Understanding the impact of animated gesture performance on personality perceptions. ACM Transactions on Graphics, 36(4), Article 128. https://doi.org/10.1145/3072959.3073697

Introduction and Background

i) “Hey, my name’s Julian Stassi and I’m 1000% committed to UCLA! I’m from Sacramento, and majoring in Business-Economics. I love watching football, hanging with friends, and I’m a huge foodie. I’m looking for a roommate and planning to rush in the fall, so bang my line!”

These exact messages flood the UCLA Class Instagram page every single year. This is a space where thousands of recently admitted students introduce themselves to find roommates and friends, and it is a great way for students to start shaping their college identity before ever arriving on campus. These posts are more than just sharing majors or hometowns; they’re filled with unique sets of carefully chosen language that says something about how students want to be seen.

ii) These personal bios are filled with informal language, which makes them feel ​​personal and distinctive. While others can be more straightforward and formal. This made us question: Does gender influence tone or slang? How are North Campus majors different from STEM majors? What connections could be made between these new Bruins, and what does this say about them?

iii) We then analyzed the first 200 posts from the official UCLA 2029 account and closely looked at the diverse use of slang, grammar, and emoji use, and how language varies across gender, major, and location. Our project explores how even small stylistic and language choices reflect deeper identity performances and social positioning within online spaces. These posts are not just about introductions; they are shaping how students want to be perceived as they begin forming who they are on campus.

Methods

For this project, like previously mentioned, we conducted our quantitative analysis by going through the first 200 posts from the @ucla2029freshman class Instagram account – a social media account used for recruiting and engaging with incoming freshman students at UCLA – and analyzed a myriad of demographics from each post.

Our main goal from this cultivation of data was to analyze the topicof linguistic strategies used to engage prospective students and to comprehend how language choices reflect broader communicative goals in higher education and social media outreach. The method of data collection, a quantitative content analysis where we carefully recorded and studied language patterns in social media posts, focused on a 200 sample from the largerpopulation of the account and looked at gender (male/female), the opening style used (how they greet the people seeing their account, e.g., hello, hiii, hey, etc), any slang used (things like words in all caps, pls, wanna HMU, roomie, foodie, insta, etc), if there is a presence of emoji use, proper grammar and punctuation, if students listed their pronouns, if people used all lowercase or all uppercase, and their intended major (pre-med, humanities, STEM).

Since we examined different styles of speech, we also drew from the idea of language variation, which looks at how people’s language changes depending on their background, age, gender, or community involvement, as well as grammar, tone, and word choice (Bahtina, 2025).

Our data collection specifically focused on the first 200 posts chronologically available on the account at the time of data collection to ensure that we cultivated a large but manageable sample representing not only a multitude of academic disciplines but also genders, communication styles, and decisions. This approach allowed us to gather a wide variety of people at different stages of the student admission process and people from an abundance of different demographics, which helped ensure an accurate sample of the representation.

When reporting findings on gender in our study, the results were strictly based on the first 200 posts from the class account, and we did not assume a 50/50 gender split. This was because we wanted to limit any confounding variables and stay stable with our procedure and data collection, and it also revealed the prevalence of social media use and how it differs across gender.

Results and Analysis

After each group member cultivated data from the posts of the class of 2029 Instagram account we found the following findings: 43.1% of female students use emojis compared to only 32.6% of male students (Figure 2, 3), female business economic majors are 50% more likely to use slang compared to men, women are 1.8 times more likely than men to write in lowercase (Figure 1), and men in humanities adhere most strongly to formal digital norms. A key concept shown here is also the informalization of language, which posits that communication tendencies on social media tend to vary in regard to their casual and playful tone (Natsir et al., 222). This is evident in the use of emojis, lowercase letters, and slang in social media posts (Figure 1).

Figure 1

From this data we had several findings – what appears to be a casual introduction or captioning on an introductory Instagram post is often a strategic act of self-presentation that differs among each person depending on their own demographics and the image they want to illustrate to the people viewing their posts which could be future friends, roommates, classmates, or even project mates in a class setting like this. Simply put, the data shows the presence of gendered linguistic performance (Van Herk, 101). This refers to the idea that is not something we simply are but something we do, which relates to the evidence because it emphasizes the presence of linguistic performance and ways people perform. While we found relationships between gender and linguistic decisions and major and self-presentation, the relationship between gender and major was much more complex than a clear pattern.

Every individual use of emoji, lowercase letter, or slang word differs person to person (however, there are more common themes seen in some demographics than others) and demonstrates some aspect or other about a person. These posts on the Instagram account aren’t just digital information, but they have the power to reflect someone’s identity, culture, and origin. Aligning with the idea that emojis are a form of cultural expression. As Professor Junnifer Prough says, emojis clearly display layers of cultural communicative meaning, explaining that users use emojis to be understood and for belonging (Ted Talk by Freedman, 2019). When students post their introductory bios, they are engaging in a form of visual and linguistic identity making, whether they choose to or not.

Figure 2

Figure 3

These results and implications are imperative to helping illustrate how social norms shape larger themes across digital communications and reinforce the identity that language is performative even in the most casual of settings.

These students engage in what is known as “front stage” performances where they craft online personas that balance authenticity, approachability, and cultural fluency within the norms of the current contemporary society and how Gen Z acts in the current state of the social media culture. The agentive behavior is consistent with research that shows the use of social media to develop self-presented messages tailored to specific audiences, shaping their identity even before arriving on campus (DeAndrea et al., 2011).

Discussion and Conclusion

Our analysis of the UCLA Class of 2029 Instagram posts shows the language in Instagram posts as a form of digital identity construction. While captions appear to be informal, they actually reveal a choice that every single student makes in order to express themselves. They do this in order to, in some way, fit in or stand out. The use of emojis, punctuation, and slang in order to differentiate genders, majors, and regions shows that language use is made purposefully. The pattern that was most clear to us was gender-based differences in tone and formatting of the posts. Female students, when compared to male students, overwhelmingly use an informal style of using emojis, lowercase, and slang. Males, on the other hand, were more likely to have proper grammar and tone. This is clear in the research with sociolinguistics showing women often are more linguistically innovative in language to build social standing than men, who look toward status-oriented forms of communication. The difference between majors was also an interesting point where humanities students had more flexible tones and relaxed language, while STEM students were direct. This shows how different disciplines socialize students into a variety of ways in which they communicate. These posts are not only explaining who they are or what they are excited for, but they also create a performance of sorts with the things they put within the text caption of their posts. The slang, punctuation, and emojis all say something about the way in which the students desire to be seen as they matriculate.

References

Bahtina, D. (2025). 2A Variation in language. Communication 188B.

DeAndrea, David C., et al. “Serious Social Media: On the Use of Social Media for Improving
Students’ Adjustment to College.” The Internet and Higher Education, vol. 15, no. 1,
2012, pp. 15–23. https://doi.org/10.1016/j.iheduc.2011.05.009.

Freedman, A. (2019, April 26). The culture of emoji. ??? | Alisa Freedman | TEDxUOregon. YouTube. https://www.youtube.com/watch?v=U1QpAUhnoWE

Natsir, Nur, et al. “The Impact of Language Changes Caused by Technology and Social Media.” Language Literacy: Journal of Linguistics, Literature, and Language Teaching, vol. 7, no. 1, 2023, pp. 220–28. https://pdfs.semanticscholar.org/9216/d49e850423f6d38e416694724061649445ec.pdf.

Van Herk, G. (2018). Gender. In What is sociolinguistics? (2nd ed., pp. 96–116). Wiley Blackwell.

Duggan, Maeve. (2013, September 12). It’s a woman’s (social media) world. https://www.pewresearch.org/short-reads/2013/09/12/its-a-womans-social-media-world/

Introduction and Background

Generation Z (“Gen Z”) is often seen as the generation that is constantly challenging traditional norms, especially when it comes to how they speak. Over the past couple of years, TikTok has been a cultural dominant, where slang spreads rapidly and often carries deeper meanings about identity, relationships, and culture. Prior research has explored gender differences in communication; however, they have mostly focused on face-to-face or text-based interactions. We believe that far less is known about how gendered language plays out in fast-moving, algorithm-driven spaces such as TikTok. Hence, what led us to conduct this research, our target group consists of Gen Z women and men ages 18-25 who are active users on TikTok. We specifically selected TikTok due to its platform population hosting more Gen Z individuals than others, and due to the constant exchange of slang on its platform. Common linguistic features of Gen Z include shortened words and abbreviations such as “sus”, for suspicious. Other linguistic features present include gendered slang phrases that reinforce traditional gender expectations, such as the terms “girl boss”, “I’m just a girl”, “sigma male”, etc.

Some academic sources we view to be relevant to our topic include Van Herk’s “What is Sociolinguistics?”, which focuses on differences between gender interactions and communication. Herk explains that gendered language is not natural but performed, since gender is a social construct. He also points out that women most commonly use hedges, fillers, tag questions, uptalk, etc, that reflect differences in the way women and men communicate. In comparison, men tend to be more assertive and interruptive. This source helps us understand the roots of gendered communication so we can then compare it to modern slang use and its relation to gender. Another source we are closely looking into is, “The Social Significance of Slang” by Alice Damirjian. This article argues that slang use is deeply tied to identity formation, group boundaries, and social cohesion. While it doesn’t focus on the meaning of slang words, it instead explores how words are used and in what context. This method is similar to what we intend to do in our research paper, and why we viewed this source as a vital informative piece.

Additionally, A.M. Blackstone’s “Gender Roles and Society” article explores how gender roles are learned and reinforced through socialization and institutions. This citation we included since it helps us support our hypothesis that Gen Z slang may reflect gendered communication patterns. Blackstone’s sociological framework on gender and identity is a great source that guides our research and analysis, based on empirical evidence rather than assumptions. Overall, these studies have helped us inform our hypothesis that argues that while slang is fluid and not fully tied to gender, slang use still echoes traditional gender norms.

Methods

Our study investigates how Gen Z men and women use slang on TikTok and whether this reflects broader gendered communication patterns. To explore this, we will collect slang terms through a survey and then analyze how those terms are used in TikTok videos using a fresh account to eliminate algorithmic bias. The survey will be hosted on Google Forms for ease of delivery and to ensure that we have access to necessary statistics. After this survey, we will examine the top videos for each slang word. The use of both individual and broad-scale analysis techniques allows our group to build a more nuanced understanding of the use of slang.

Once this stage of the research process has been completed, we will be aiming for 10 videos per slang term, which will offer us dozens of relevant examples through both the video itself and its comments. This number is a reasonable amount to reach, but it does not limit our understanding. We chose this two-prong data collection method to more accurately depict the results of this experiment and gain a deeper understanding of the language used.

Using thematic coding and discourse analysis, we will analyze tone, context, delivery, and nonverbal cues associated with each slang term, focusing on how language use relates to gender performance and identity. The discourse analyzed will be specifically the way that the different genders choose to interact with each other using the slang presented. Our guiding research questions include: Do men and women use the same slang terms differently? What patterns of gendered communication emerge through slang? And how do these trends reflect or challenge traditional gender norms? Based on existing sociolinguistic literature, we hypothesize that Gen Z slang use mirrors gendered communication tendencies, with women more likely to use slang that signals inclusivity and emotional connection (e.g., “slay”), and men more likely to use slang that emphasizes assertiveness or dominance (e.g., “let’s go”). However, given Gen Z’s fluid approach to identity and language, we also expect to find challenges to this norm.

Results and Analysis

Our final pool of participants for the Google survey portion of data collection was 91 responses, with 51.6% male and 48.4% female respondents. We found that “bet” and “rizz” were the two most frequently used slang terms.  The term “rizz” was the most frequently used, with it being mentioned a total of 46 times between 17 women and 29 men. While “bet” came in second, with it being mentioned a total of 23 times between 11 women and 12 men.

Figure 1. Results from the Google Form Survey: Total Number of Respondents was 91

When analyzing the 10 male-coded videos for “rizz”, 8 out of 10 videos generated by male content creators were men demonstrating their “rizz”, by approaching women with a flirtatious attitude, with the goal of receiving the woman’s contact information. While 4 out of 10 videos captured men providing advice on how to have “rizz” or “rizz up” women. This suggests that men’s use of the term  “rizz” aligns with traditional masculine traits like assertiveness and confidence in social situations. It reflects Gen Z’s tendency to blur sincerity and parody, where young men both conform to and mock traditional courtship behavior.

Figure 2. Contextual Use of “Rizz” by Gender (Male: Flirtation, Confidence)

As for the female-coded videos for “rizz,” the results demonstrated that women most often used “rizz” for humor and romantic advice, sometimes expanding it beyond male-female contexts. The data suggests they intentionally adopt masculine slang to relate to men and navigate social dynamics, which reflects how gender norms shape communication even with shared slang. In addition, the data also showed how women resisted gendered dynamics by using “rizz” in a different manner than it was intended.

Figure 3: Contextual Use of “Rizz” (Female: Romantic Advice)

For the 10 male-coded videos with the slang term “bet,” we found that men most frequently demonstrated or recorded their use of “bet” to express agreement, acceptance, or commitment to a plan, e.g., responding “bet” when a friend proposes hanging out or making a wager. 5/10 videos analyzed showcased scenarios where “bet” was used to confirm plans or signal confidence in accepting challenges. This result suggests that men tend to use “bet” as a casual, assertive way, aligning with traditional masculine traits of confidence and decisiveness. It also reflects Gen Z’s conversational style, which blends casual affirmation with a sense of underlying confidence.

Figure 4. Contextual Use of “Bet” by Gender (Male: Agreement, Commitment, Confidence)

As for the 10 female-coded videos for the term “bet,” Our results showed that women most often used “bet” to express agreement, excitement, or playful sarcasm in casual conversations with friends. 3/10 videos analyzed women using “bet” in a lighthearted or humorous way. Showing enthusiasm or signaling they were on board with a plan.

Figure 5. Contextual Use of “Bet” by Gender (Female: Sarcasm, Excitement, Agreement)

Discussion and Conclusion

Our results show that there are distinct gendered patterns in the use of slang terms like “rizz” and “bet.” For the slang term “rizz,” men were more likely to demonstrate or embody the term, while women often used it mockingly or humorously. In the case of “bet,” men tended to use the term to affirm plans or accept challenges, reflecting direct engagement, whereas women used it more playfully or sarcastically. For both slang terms, men typically expressed traditionally masculine traits such as confidence, assertiveness, and decisiveness. In contrast, women exhibited traits like humor and irony as a way to challenge or resist the gender dynamics ingrained in the slang terms. These insights are particularly useful for scholars in sociolinguistics, digital media, and gender studies, as they highlight how informal language can reinforce, challenge, or reshape traditional gender roles. By looking at how terms like “rizz” and “bet” are used, we can gain a better understanding of how digital media reflects and reinforces ideas about traditional gender roles and communication. Our results could benefit researchers, educators, and media literacy advocates by shedding light on gendered communication patterns embedded in Gen Z slang. This insight can contribute to a broader conversation about how digital culture affects youth identity formation, peer dynamics, and societal expectations. Our research helps unpack the cultural significance of everyday language, positioning it as a key site for both reproducing and potentially resisting dominant gender ideologies.

References

Bibian Ugoala. “GENERATION Z’S LINGOS on TIKTOK: ANALYSIS of EMERGING LINGUISTIC STRUCTURES.” Journal of Language and Communication, vol. 11, no. 2, 30 Sept. 2024, pp. 211–224, www.researchgate.net/profile/Bibian-Ugoala/publication/384965246_GENERATION_Z, https://doi.org/10.47836/jlc.11.02.08.

Blackstone, A. (2003). Gender Roles and Society. https://digitalcommons.library.umaine.edu/cgi/viewcontent.cgi?params=/context/soc_facpub/article/1000/&path_info=Blackstone___Gender_Roles_and_Society.pdf

Damirjian, A. (2024). The social significance of slang. Mind & Language. https://doi.org/10.1111/mila.12530

Herk, G, V. (2018). What Is Sociolinguistics? (Linguistics in the World) 2nd Edition (1). India New Delhi: Wiley Blackwell.

Jahan, I. (2021). The impact of gendered language on our communication and perception across contexts and domains. Journal of Language and Linguistic Studies, 17(4), 3523-3534. https://www.jlls.org/index.php/jlls/article/view/5449

Introduction and Background

Stereotypes associated with gossip divert from its basic communicative, relational, and cultural functions. Gossip is constantly misunderstood as idle chatter in scholarly as well as popular discourse. Recent research in psychology, communication science, and organizational behavior has reframed gossip as a socially strategic action. Gossip has been shown to be critical to social coordination, identification, and norm enforcement as a primary way in which individuals acquire knowledge about both others and themselves (Dores Cruz et al., 2021). Through our study, we examined these ideas from the specific perspective regarding how gendered depictions of gossip have evolved across generations within popular media, namely television dramas.

Before looking into this, we were already aware of previous information regarding gendered patterns of gossip, i.e., the idea that women and men gossip differently. Past research characterized women as gossiping primarily about relationships and personal matters so as to participate in social bonding, whereas men gossip to acquire humor or attain status (Levin & Arluke, 1985). Current research maintains this trend, with women participating in emotion-focused, relation-directed means of gossip in the context of coalition-building (Davis et al., 2018). We also know that men, on the other hand, gossip far less overall and use gossip in instrumental functions as a way to navigate social positioning. Such behaviors cohere with Deborah Tannen’s theoretical framework, distinguishing “rapport talk”, a related, connection-directed characteristic of women, and “report talk,” an informational, hierarchical characteristic of men (Van Herk, 2018).

Despite the fact that such patterns have long since taken root, there was no framework to comprehend the way in which media representations reinforce or challenge these gendered communication norms in the long run–the leading question guiding our own research. While prior research has explored gendered patterns in gossip, few studies have examined whether and how gossip has evolved across generations or been portrayed differently over time in television. This gap in the literature motivated our study, as we aimed to investigate whether shifts in gender norms were mirrored in media discourse. With continued influence from television to the public eye regarding social conduct, the issue we examined involved whether gender representations in gossip have shifted in sync with gender norms. With this, our research documents the construction of gossip across two periods (1990s–2000s, 2009–2022) in U.S. television with attention to gender. By combining empirical content analysis with sociolinguistic theory, our analyses help demonstrate the idea that gossip is neither fixed nor gendered; it is an evolving social practice.

Methods

In terms of gossip across different generations and genders, we were more interested in how TV shows categorized gossip across two distinct periods and how female-identifying individuals differed in their communication features from male-identifying individuals. First and foremost, we coded for gender identity based on the pronouns that were used in the show. We analyzed different TV shows representing two generational periods. The first period involved shows that were released between 1997-2009, including Friends (Seasons 5 and 8) and Survivor (Season 6). The second period involved TV shows released between 2009-2022, including Love Island (Seasons 1 and 2), Outer Banks, and The White Lotus. All of these episodes were accessed through streaming platforms, including Netflix and Hulu. Because television remains a powerful force in shaping public understandings of identity and interaction, analyzing TV dialogue allows us to observe how gossip reflects or resists evolving social norms.

For each of these shows, we chose approximately three scenes, each around 2 minutes in duration, that featured confrontation, gossip, or situations that all displayed differences between how the two identities communicated with one another. A total of 15 scenes were analyzed and transcribed across all shows. By observing the contrast between individuals, there was an exposure to how gossip can be challenged, and it allowed us to gain insight into each generational period. So, we assessed the prevalence of communication features in the scenes in the two periods of time.

*See Figure 1 below for an example of our transcriptions.*

Figure 1. Transcription from Friends (Season 5, Episode 9), showing a gossip scene used to analyze gendered communication styles like humor and confrontation.

Each television scene was analyzed using six communication features, each previously associated with gendered communication and gossip behavior: indirectness, report, rapport, humor as a shield, status assertion, and meta-commentary. For example, we see indirectness in Love Island when Caro and Cashel are talking about other couples as well as themselves. Caro, who identifies as female, says “ °hh I just (0.3) feel like (0.4) you’re not being ↑honest with me.” Use of the words “I just feel like” indicates hedging, suggesting Caro’s unwillingness to be straightforward due to nerves about how her words may be perceived. In response, Cashel, who identifies as male, says “ <<laughing> I guess I’m just the worst boyfriend ever.>” He uses humor as a shield to avoid taking ownership of his behavior. We also observed a report talk in Friends, when Ross asks, “What’s going on?” to get a factual explanation of the situation, contrasting with rapport talk, like Harper in The White Lotus confiding in Ethan to build emotional alignment over shared social discomfort. Status assertion occurred in Survivor, where one contestant claimed, “They’re playing us,” in an attempt to establish control over the narrative. Lastly, meta-commentary was seen in Outer Banks, when a character prefaced gossip with, “I know we’re being shady, but hear me out…” acknowledging the act of gossiping itself.

Figure 2. Bar chart comparing six gossip features across male and female characters from two TV generations (1997–2009 and 2009–2022), based on average frequency.

Figure 2, a grouped bar chart, compares the previously mentioned communication features across male and female characters in TV shows from two time periods: 1997–2009 and 2009–2022. The X-axis contains the coded communicative traits, while the Y‑axis shows their average frequency on the 0–4 scale. The pattern is striking: use of gossip communicational features by female characters in TV shows remained relatively consistent across the periods, while portrayals of male gossip noticeably shift, especially in regards to a reduced use of humor and indirectness. This suggests a slow blending of gendered language styles, even as clear differences persist.

In addition to data, we analyzed specific TV scenes to demonstrate these trends across contexts. Figure 3 features a moment from the White Lotus, between husband and wife, Ethan and Harper. In one scene, Harper attempts to gossip with Ethan about the other couple they are traveling with, whom she sees as fake, snobby, and arrogant (White, 2022). She uses an indirect style of gossip to assert her status as well as gain rapport from her husband, exemplifying the modern portrayal of female gossip both strategically and socially.

Figure 3. Scene from The White Lotus (Season 2, Episode 2), showing indirect and strategic gossip between characters Harper and Ethan.

To situate our project within real-world discourse, we included several informal references. A TEDx Talk titled “Why gossip is good” by Assem Bisenbay breaks down gossip’s benefits in modern society (Bisenbay, 2019). Another TEDx video, “The virtues of gossip” by Richard Weiner, echoes these ideas by arguing that gossip can foster social cohesion (TEDx, 2013). Additionally, a Reddit thread asking “Why do we love gossip?” offers everyday perspectives that parallel our findings about social bonding and status (CommonRash, 2022). Taking this media into account, our project was structured around five key ideas: gendered gossip, generational communication, TV media discourse, sociolinguistic method, and report vs. rapport talk. These pinpoint our population (TV characters), method (scene-based communication coding), and theoretical orientation. All TV show clips analyzed were publicly available; no private data or human subjects were involved. Our research is the collaborative work of Abigail Garza, Julian Goldman, Faye Turcotte, Madeline Doring, and Dylan Sherr, conducted under the mentorship of Professor Bahtina.

Discussion and Conclusion

Our findings across various scenes in TV shows contribute to the idea of gossip as a whole and what it truly means to privately discuss personal information with others through means of conversing. Gossip itself provides key insights into the ways in which individuals interact on a broader scale, both culturally and socially. In terms of gender and generational differences, studying gossip across all individuals can be used to highlight key aspects of the progression that can be seen in conversational analysis across genders. Through studying numerous television dramas, it can be seen that the ideas of report and rapport amongst male-identifying and female-identifying individuals remain true no matter the time period. This report vs. rapport stereotype can be generally accepted as being a ‘mainstay’ in the scene of gossip itself. So, although there are constant changes occurring in the world, there will still be aspects of gendered gossip that remain constant no matter where we are or what time it is.

References

Bisenbay, A. (2019, September). Why gossip is good [Video]. TED Talks. https://www.ted.com/talks/assem_bisenbay_why_gossip_is_good?utm_campaign=tedspread&utm_medium=referral&utm_source=tedcomshare

Burnett, M. (Executive Producer). (2003, April 3). Girls vs. boys (Season 6, Episode 8) [TV series episode]. In Burnett, M. (Executive producer), Survivor. CBS.

CommonRash. (2022). Why do we love gossip? Reddit. https://www.reddit.com/r/CasualConversation/comments/v9dyen/why_do_we_love_gossip/

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Introduction and Background

When deciding which videos to use for our analysis, there was an initial limitation to our study related to cropping longer videos for brevity and how that would affect audience perceptions of the apologies. With Colleen’s video, for example, we cropped her 10-minute video into a 4-minute video and decided that the middle of the video was a good way to gauge the overall language use. This decision aligns with Ambady and Rosenthal’s concept of thin slices, which suggests that people can accurately judge complex traits such as sincerity or emotional state from brief snippets of behavior. By focusing on a representative portion of the video, we aimed to preserve the essence of the apology while still enabling meaningful analysis grounded in the reliability of these short behavioral samples. (Ambady & Rosenthal, 1992)

Our contribution lies in bridging rhetorical analysis with audience perception, using YouTube apology videos as a case study to explore how sincerity is communicated and interpreted in digital spaces. By analyzing apology videos from these “influencers,” we aim to investigate not only what these public figures say, but how they say it (visually, emotionally, and linguistically). Our thesis is that public apologies are performative acts in which specific communicative choices (like a tearful tone, minimal makeup, or carefully crafted phrasing/scripting) shape whether an audience sees the apology as genuine or manipulative. This project sheds light on how the intersection of image, tone, and language affects credibility in the age of viral accountability and offers a nuanced perspective on the performance of remorse in online culture.

Methods

To examine how public figures convey sincerity in their apology videos, we selected three widely circulated YouTube apologies from the previously mentioned figures. We then distributed these clips to 30+ college students via an open-ended and multiple-choice Google form survey. Participants were asked to reflect on their impressions of the apologies’ sincerity, whether they believed the public figure should be forgiven, and what verbal or nonverbal elements shaped those judgments. Our analysis was guided by two core theoretical frameworks: interpersonal apology theory and Benoit’s image repair discourse (Sandlin, J. K. et al., 2018). Interpersonal apology theory, rooted in communication studies, outlines five key components of a sincere apology: Admitting fault – clearly acknowledging responsibility for the offense, Acknowledging harm – recognizing the damage done to others, Expressing remorse – showing emotional regret and guilt, Asking for forgiveness – signaling a desire to make amends, and Offering compensation or corrective action – providing a tangible or verbal commitment to change.

These components emphasize the relational and emotional dynamics between the offender and the audience, underscoring that sincerity is not just about what is said, but how it’s expressed. To evaluate rhetorical strategies, we applied Benoit’s image repair discourse theory(Sandlin, J. K. et al., 2018). This framework categorizes how individuals and organizations respond to crises through specific strategies, including: Denial (refusing responsibility or shifting blame), Evasion of responsibility (claiming lack of intent or knowledge), Reducing offensiveness (minimizing the severity or attacking accusers), Corrective action (promising to fix the issue), and Mortification (openly admitting guilt and asking for forgiveness).

These strategies are often used in combination and serve to repair the speaker’s public image. By identifying which of these strategies were present in the videos, we could compare them with how participants responded in terms of perceived sincerity and forgiveness.

We also paid attention to nonverbal and contextual cues, such as facial expressions, vocal tone, emotional displays (e.g., crying), clothing, setting, and even the presence or absence of makeup. These elements were analyzed to understand how visual and tonal choices contributed to the perception of sincerity, whether, for instance, a more casual appearance or a somber tone enhanced credibility. We used a dual-method approach to analyze how public figures use specific linguistic and visual strategies in their public apology videos on YouTube to influence the audience’s perception of sincerity, accountability, and forgiveness.

Results and Analysis

Drawing on Benoit’s image repair discourse theory and interpersonal apology theory, we performed a content analysis of the three YouTube videos, focusing on four specific aspects: the influencers repetition of performative verbs (“sorry” or “apologize”), their emotional appearance, denial, and personal presentation to help us better visualize and interpret the survey results (Sandlin, J. K. et al., 2018). We then used a Likert-type scale of 1-10 to measure our perceived perceptions of these four variables (see Table 1), rating 10 as the highest level perceived and 1 as the lowest level perceived. For example, in Table 1, Laura Lee received a 10 for Repetition Level of performative verbs, meaning she repeated the verbs “sorry” and/or “apologize” over ten times. 

Table 1

Perceived level of linguistic and visual features in influencer apology videos (1 = low,10 = high). Levels rated are based on content analysis of all three apology videos.

	Logan Paul	Colleen Ballinger	Laura Lee
Repetition Level of Performative Verbs	6	1	10
Visually Emotional Level	5	2	9
Denial Level	1	8	1
Personal Presentation Level	1	3	1

Survey Results

The other method that we used in our dual method approach was an open-ended online survey. To better visualize how the audience rated the sincerity/accountability of the video, we included one of the responses to our question asking the audience “On a scale from 1 to 7, how sincere/accountable do you find the video?” (1 = not sincere at all, 7 = took full accountability). Highlighting the most significant findings from this question, we found that 60% of surveyors did not find Colleen Ballinger to be sincere/accountable (see Pie Chart 1). We then found that 50% of surveyors found that Logan Paul was somewhat sincere/accountable (see Pie Chart 2). Finally finding that 100% of surveyors did not find Laura Lee sincere/accountable (see Pie Chart 3).

Pie Chart 1

Measuring audiences’ perception of the sincerity of Colleen Ballinger’s apology video (respondents either choose 1 or 3).

Pie Chart 2

Measuring audiences’ perception of the sincerity of Logan Paul’s apology video (here we see a bit more variation in responses).

Pie Chart 3

Measuring audiences’ perception of the sincerity of Laura Lee’s apology video (here we see a unanimous decision).

Measures of Audience Perception:

To better understand the significance of the survey responses and to have clear numerical data, we then used a Likert-type scale of 1-10 to quantify the audience’s free response answers (see Table 2).

Table 2

Audiences’ perceived level of sincerity, forgiveness, accountability, and their changed perception (1 = low, 10 = high). Levels rated are based on free-response answers from open-ended surveys.

	Logan Pual	Colleen Ballinger	Laura Lee
Perceived Sincerity Level	5	2	3
Changed Perception Level	2	1	1
Forgiveness Level	3	1	2
Perceived Accountability level	7	5	2

We, from quantifying audiences free-response questions into a Likert-type scale, were able to see a clear trend. In the videos where the influencers received higher numbers on our content analysis scale, audience members were more likely to rate sincerity levels lower. Meaning, influencers who were visually more emotional, used more repetition of words such as “sorry”, and who expressed more denial of wrongdoing, were found by the audience to have less sincere apologies. The audience was also likely to rate the accountability level lower (see Table 2). For Logan Paul, responses were more mixed, though they mostly leaned negative or unchanged. For Laura Lee, the majority of participants reacted very negatively, describing the apology as overly emotional, manipulative, or performative. Finally, for Colleen Ballinger, we found that the apology reinforced or worsened existing negative opinions, even if they had already stopped watching her (likely due to the use of a guitar and breaking out into song, which can come off as dismissive and playful during a serious situation). Overall, we were able to see that Logan and Laura took more of an interpersonal route of apology (5/5 components of IAT), whereas Collen was geared more towards image repair (4/5 components of IRDT), which heavily affected audience perception of sincerity.

Some things to note when looking at such apologies are that “The medium is the message”. This reminds us that how an apology is delivered (through a platform like YouTube) shapes audience perception just as much as the content of the apology itself. (McLuhan, 1964)

Discussion and Conclusion

In conclusion, we considered audience commentary on YouTube as part of the broader discursive context. Comment sections often revealed whether viewers thought the apology was believable or performative, and frequently referenced the public figure’s prior reputation. This ties into the two-step flow model, which suggests that public opinion is shaped not just by media content but by influential opinion leaders (for example; top commenters or media coverage) who interpret and amplify messages for others. We also acknowledged the mass-personal nature of YouTube apologies (where personal disclosures are made in mass communication formats) and how this shapes expectations of authenticity and vulnerability. (Lazarsfeld, Berelson, & Gaudet, 1944)

References

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