Sociolinguistics

Cydney Jover, Daelyn R Johnson, Mia Dibono, Yexalen Casas, Ashanti Bracamontes

Over time, as a society, we have seen a general increase in online and digital communication. Since online communication has become more mainstream and a key format of expression that is universally common among society is the expression of laughter, the main focus here is the study of digital laughter in the form of specific expression, including “lol”, “LOL”, “haha”, “HAHA”, “hehe”, “LMAO”, or “😭”- to name a few. Typically, these phrases are used in social encounters digitally to convey laughter or humor. What we aim to acknowledge in this research project is how these specific phrases are used both similarly and differently as forms of digital laughter among Gen Z and Gen A communities. We wanted to dive deeper into how digital laughter slang can fluctuate in meaning depending on the social context, as well as the speaker’s generation or age. This research project focused on studying the sociolinguistic aspects of digital laughter and humor, as well as how specific phrases and emojis could indicate differing social meanings depending on specific factors, including generation, age, social context, and scenario.

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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

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Jura Glennie, Ryan Gorji, Mikaela Edwards, Zahra Umar, Lizett Hernandez

Have you ever received a text that just said “okay.” and spent the next hour wondering if someone is mad at you or if you’re just being too Gen Z about it? These kinds of reactions highlight how digital communication is often interpreted through generational lenses that can drastically shift meaning and connection in digital conversations. In this study, we investigate how generational differences affect the interpretation and use of digital features in text-based interactions. The research examines how Generation X (born 1965-1980) and Generation Z (born 1997-2012) understand and express digital body language through the use of punctuation, capitalization, emojis, and acronyms. We hypothesize that Gen Z will use more expressive forms of digital body language while Gen X will favor more minimal or formal styles, since they did not grow up in the digital age. This study focuses on how these generational groups perceive emotions, the reasoning behind selected features, and relationship-based decisions in digital communication. Previous research shows that nonverbal cues were created and popularized by younger generations, making them more recognizable to Gen Z, which aligns with our study’s findings. The takeaways from our results suggest that while digital features are identifiable amongst these age groups, their generational differences shape their communication style and interpretations.

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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

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Mariam Arafa, Bianca Richmond, Olivia Rubin, Sydney Steinger

In the workplace, a new female intern might wonder, Why does my male boss communicate with me so differently compared to my male coworkers? Our research explores this question. Communication in the workplace is not just exchanging information; rather, it reveals social hierarchies, implicit bias, and power and gender dynamics. This study focuses on how gender and professional experience influence communication in the workplace. Working off existing literature, we examine how men often use “report talk”, assertive and task-oriented communication, and women use “rapport talk”, communication based on connection and emotions. While we were able to find research on gendered communication patterns, studies were limited in addressing how age and experience alter these patterns. To bridge this gap, we conducted a survey and interviews targeting professionals of various genders, industries, and levels of experience. Our results defend three patterns: (1) same gender communication is usually more relaxed and informal; (2) supervisors speak more formally and respectfully when addressing more experienced employees; and (3) long-term employees that have an established relationship with their boss are addressed with continued respectful but less formal communication over time. Our study provides evidence that it is not just gender that shapes workplace communication, but also experience, which subtly impacts hierarchies and norms in professional interactions within the workplace.

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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

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Justine Fisch, Sarah Barsamian, Joselyne Hernandez, Yarina Andrade, Lesly Cabrera

What can a single review say about a professor or, more importantly, what can it imply? Today, anonymous student reviews play an increasingly crucial role in shaping a professor’s reputation, especially on platforms like Bruinwalk. Beneath the surface of these brief comments, however, lies a deeper question: are these evaluations truly about performance, or do they highlight gendered assumptions students unconsciously carry? Our study examined how the emotional tone and perceived sentiment of Bruinwalk reviews shape students’ assumptions about a professor’s gender. We analyzed ten anonymized reviews (five for female STEM professors, five for male) and surveyed 33 participants, asking them to rate emotional language, identify review sentiment, and guess the professor’s gender. Contrary to our hypothesis, highly emotional reviews were not overwhelmingly associated with female professors. However, positive reviews were disproportionately perceived to be written about female professors, revealing a strong bias linking positivity with femininity. While participants guessed professor gender with only 60% accuracy, their assumptions consistently reflected typical social expectations. These findings suggest that even when gendered language isn’t present, the perception of gender still shapes how we interpret emotion, authority, and professional competence in academic settings.

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Introduction and Background

At UCLA, Bruinwalk has become a popular platform where students share their experiences, often influencing others’ decisions on which professors or classes to take. However, while these reviews may seem like casual reflections, they can also reveal underlying biases, including gender stereotypes that shape how students describe their professors. Past research has shown that female professors are often judged more on their likeability, warmth, and personality, while male professors are often judged on their authority and expertise (Mitchell & Martin, 2018). Although much of this research focuses on formal evaluations, less is known about whether these same patterns show up in online, informal reviews where students write anonymously. Our study addresses that gap by examining whether students use more emotionally charged language when reviewing female STEM professors compared to male professors on Bruinwalk. By analyzing hyper-emotional language, tone, and word choice, we aim to better understand how gendered assumptions may still shape students’ perceptions, even when reviewers are not directly asked to evaluate gender.  Our research will attempt to identify if language bias, rooted in gender stereotypes, affects how UCLA students evaluate instructors. Furthermore, we are curious to explore whether students tend to leave more emotionally charged reviews for female professors due to social norms that expect women to be more nurturing or emotionally expressive. This idea is present in a study by Basow et al. (2005), where researchers concluded that gender bias may manifest in academic contexts and that stereotypes, particularly for female professors often shape student perceptions.

Methods

Our study examined how the gender of professors influences the types of language used in student reviews, with a specific focus on hyper-emotional language. According to Hinojosa et al. (2019), hyper-emotional language includes emotionally charged adjectives, overstatements, and highly subjective expressions and we use this same definition in our survey.The analysis aimed to determine whether students are more likely to use emotionally charged positive or negative language when reviewing female STEM professors compared to male professors on Bruinwalk, a rating platform used by UCLA students. We randomly selected a total of five female and five male professors from various STEM fields. For each professor, one student review was chosen using a random number generator, resulting in ten reviews for analysis in our survey. 

Before including the reviews in our survey, we removed all gender identifying terms, such as pronouns and names to ensure anonymity and reduce any form of bias. This allowed participants to make judgements based only on the language used in each review. We then created a survey using the reviews and collected responses from 33 participants.Each participant answered three questions for each review, (1) rating the emotional level using a labeled 5-point Likert-type scale, following the methodology of Basow et al. (2006),ranging from “no emotion” to “most emotion,” (2) they identified the perceived gender of the professor based on the review, and (3) they labeled the review as either positive or negative. 

The observable communication and language aspects central to our study were word choice, tone, and emotional intensity. Reviews varied in their placement on the emotional scale, with some displaying stronger emotionality than others. Specific word choices often indicated whether a review was positive or negative, but the analysis also aimed to determine whether such language influenced perceptions of the professor’s gender. Beyond word choice, the tone of the review could shape participants’ impressions of the professor, potentially revealing underlying gender associations. This approach allowed us to compare how students interpreted emotional tone in reviews and whether certain linguistic patterns led them to associate a review with a specific gender.

The observable communication and language aspects central to our study were word choice, tone, and emotional intensity. Reviews varied in their placement on the emotional scale, with some displaying stronger emotionality than others. Specific word choices often indicated whether a review was positive or negative, but the analysis also aimed to determine whether such language influenced perceptions of the professor’s gender. Beyond word choice, the tone of the review could shape participants’ impressions of the professor, potentially revealing underlying gender associations. This approach allowed us to compare how students interpreted emotional tone in reviews and whether certain linguistic patterns led them to associate a review with a specific gender.

Results and Analysis

Emotionality vs. Gender:

Our analysis of emotionality in Bruinwalk reviews yielded results that slightly differed from our initial hypothesis. We had expected that reviewers would associate heightened emotional language more frequently with female professors. However, among reviews rated with the highest emotionality scores (4s and 5s), the distribution of gender assumptions were nearly even, as female professors were guessed 51.5% of the time and male professors at 50.9%. Within this sample, Figure one suggests that students do not appear to strongly associate either gender with more emotional reviews, at least in terms of direct emotional language. 

Figure one

Figure two

Positive and Negative vs. Gender:

In contrast, we observed more distinct gender patterns when analyzing the tone of the reviews, specifically whether they were perceived as positive or negative. As reflected in Figure two, Reviews that were interpreted as positive were associated with female professors 73% of the time, while only 26% were attributed to a male professor. Conversely, when reviews were perceived as negative, 43% guessed the professor to be female, and 56% guessed the professor to be male. Within our sample, these findings indicate a notable bias in how students associate gender with sentiment. As reflected by Figures three and four, a review written about a male professor was interpreted as positive by 93.9% of participants, yet 81.8% of them still assumed the professor was a woman. This pattern may suggest a strong link between positivity and femininity in students’ perceptions of reviews, as this trend remains fairly consistent throughout our data.

Figure three

Figure four

Guessing of Professor’s Gender: Lastly, we found that students were able to correctly guess the professor’s gender approximately 60% of the time. While slightly better than chance, this accuracy rate was lower than we had expected. Therefore, this indicates that while students may make gendered assumptions based on emotionality or tone, they are not consistent at accurately identifying a professor’s gender solely from written reviews.

Discussion and Conclusion

Our research teaches us how respondents’ perceptions of student reviews of professors and professor gender reflect gendered social and gender norms. Although this is a sample, we cannot assume that our findings are generalizable; our results suggest that the perceived sentiment by respondents in reviews affects gender perception, reinforcing gendered cultural and social norms. Women are expected to be warm, kind, and nurturing; therefore, respondents associated positive reviews with women. On the other hand, men are linked to criticism, assertiveness, and harshness, so respondents associated negative reviews with male professors. Our research suggests that gendered expectations influenced the perceived gender of the professor. Moreover, our research reveals that participants are unable to accurately identify the gender of the professor. This shows us that gender norms are not enough to assume gender. Lastly, our research suggests that emotionality within reviews is not gendered. Emotional language was used to describe female or male professors alike, and is not an indicator of professor gender.

Bruinwalk reviews are often taken into consideration by students to determine whether or not they should take a class. Student reviews are often littered with biases and have the ability to affect a professor’s reputation, even if the review is not representative of their actual teaching methods. Our research suggests that ratings may be born out of professors failing to meet students’ ideas of what their gender roles should be. In the future, we could research the intent behind students leaving reviews on Bruinwalk. Moreover, from research by JoAnn Miller and Marilyn Chamberlain (2000), we see that students have different perceptions of female and male professors and thereby different expectations. Expanding on Miller and Chamberlain’s research and using some of the data we have found in our research, we could expand on how perceptions of professors, based on their gender, shape student reviews.

Relevant Information:

In, “The Effects of Gendered Occupational Roles on Men’s and Women’s Workplace Authority,” by Jim Logan, dives deeper into the analysis of how gendered expectations can affect men and women’s authority in the workplace. After observing the emotionality of the language in BruinWalk reviews and how they seem to stem from the professor’s gender expectations, it is interesting to see how the same expectations can affect their authority.

In “Emotional Expression and Gender: How Men and Women Differ in Showing Emotions,” the article describes how the expressions of emotion are taught at a young age and how they come to shape our own expectations of who should express certain types of emotions. The article explores how we attribute certain emotions to specific genders, creating and enforcing gender roles.

References

Basow, S. A., & Montgomery, S. (2005). Student ratings and professor self-ratings of college teaching: Effects of gender and Divisional Affiliation. Journal of Personnel Evaluation in Education, 18(2), 91–106. https://doi.org/10.1007/s11092-006-9001-8 

Basow, S. A., Phelan, J. E., & Capotosto, L. (2006). Gender Patterns in College Students’ Choices of Their Best and Worst Professors. Psychology of Women Quarterly, 30(1), 25-35. https://doi.org/10.1111/j.1471-6402.2006.00259.x (Original work published 2006)

Hinojosa, J. A., E. M. Moreno, and P. Ferré. “Affective Neurolinguistics: Towards a Framework for Reconciling Language and Emotion.” Language, Cognition and Neuroscience 35, no. 7 (June 5, 2019): 813–39. https://doi.org/10.1080/23273798.2019.1620957.

Miller, J., & Chamberlin, M. (2000). Women Are Teachers, Men Are Professors: A Study of Student Perceptions. Teaching Sociology, 28(4), 283–298. https://doi.org/10.2307/1318580

Mitchell, K. M. W., & Martin, J. (2018). Gender Bias in Student Evaluations. PS: Political Science & Politics, 51(3), 648–652. Cambridge University Press, https://doi.org/10.1017/S104909651800001X.

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Kayla Rezazadh, Elina Ghaem Maghami, Chloe Zhao, and Lina Muller

Parting ways is rarely ever easy, but how we decide to terminate a romantic relationship can speak volumes about who we are, how we process our emotions, and the ways in which gender norms have influenced us. In times of heartbreak, some people might pick up the phone and dial their number, or even write out a lengthy text message. Others may keep it brief, or even vanish without a word. In this project, we wished to investigate how men and women initiate and navigate romantic endings both in person and in the digital world. We sent out a survey that asked participants ages 18-25 about their past experiences breaking up and being broken up with, as well as hypothetical scenarios on how they would handle the termination of short-term and long-term relationships. By analyzing the method of communication, followed by body language, tone, and level of directness, we were able to uncover differences in the extent of emotional expression between young men and women. 

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Introduction and background

Breakups are rarely easy conversations, and how we communicate during them can profoundly shape the emotional outcome for both partners. Yet while much attention has been given to how relationships form, less is known about how they end and the role that communication plays in that process. In particular, gendered patterns in communication may shape how people express emotions, manage conflict, and seek closure when ending a relationship. Are women more likely to communicate openly and directly during a breakup, perhaps choosing a thoughtful conversation or in-person dialogue? And are men more likely to lean on indirect methods like ghosting or a quick text to avoid confrontations? Based on prior research and our observations, we hypothesized that these gendered tendencies would still appear among young adults today, even in casual dating and digital contexts. Prior research suggests that gendered socialization continues to shape how people manage difficult conversations. Women tend to report higher emotional expressivity and are more likely to value open communication (Ubando, 2026), while men often internalize norms that discourage emotional vulnerability (Cinardo, 2011; Drury, 1999). However, much of this work has focused on conflict within relationships rather than the moment of actually ending it. Our project seeks to fill this gap by exploring how gender influences the communication strategies on how adults choose when ending romantic relationships, especially in today’s digital landscape. Through this research, we hope to shape modern parting practices and how greater awareness of these patterns could foster healthier, more empathetic endings to relationships.

Methods

For our method, we created a Google form survey with 35 individuals between the ages of 18 and 25, and we presented our participants with four different hypothetical break-up scenarios, where each one varied by the length of the relationship. We proposed two hypothetical questions where participants would answer based on their preferred communication style if they were in a short-term relationship. Furthermore, we asked two hypothetical scenarios based on long-term relationships and what their communication style would be. The modes of communication we provided for the answers were digital versus in-person. According to “Gender and Conflict in Long-Term Romantic Relationship,” Hamlin conveys that “…another interesting component to improve future research includes examining how length of relationship impacts relational conflict and the type of conflict style exhibited in couples” (Hamlin, 2018). His assertion aligned with our method and findings that our goal in providing hypothetical scenarios was to elicit the modes of communication our participants would prefer when they were faced with relationship termination, whether it was short-term or long-term. Through this, we analyzed the observable elements of communication, whether that directness versus indirectness (ghosting, short messages, long messages, or phone calls) and their tone, whether they were more likely to be sympathetic with their partner or more apathetic. Through analyzing Ogolsky’s research he conducted on the the progression of college student romantic relationship, he found that “young adult relationships in the 21st century are deemed as overwhelmingly casual, with the termination of the relationship typically appearing at the 4th stage of dating labeled where conflict or obstacles either end or strengthen the relationship” (Ogolsky et al., 2025). This was useful for my group and me to examine more closely self-behavior and whether it was more common for a certain gender to be more indirect and less open in their communication style. Before presenting our hypothetical scenarios, we also asked our participants to reflect on their most recent relationship, specifically how it ended, who ended the relationship, and the form of communication used for the termination. We were able to compare whether their communication styles in their most recent relationship were similar or different from their responses in the hypothetical scenarios. Through using this method, we were able to analyze the observable elements of communication styles and analyze the differences and patterns across genders when it came to preferred communication styles in the modern dating world.

Results and Analysis

After conducting our survey, we found that our results were consistent with our predictions. It is a matter of fact – women are typically more emotional and expressive when it comes to relationship termination than men are. In our survey, one of the first questions participants answered was: How would you describe your communication style during the breakup? (In regards to their most recent breakup). Interestingly, 66% of women said they were direct and emotionally expressive, and only 11% reported being direct in their communication but emotionally restrained. Contrastingly, only 29% of men reported being direct and emotionally expressive, reporting much higher levels of emotional restraint at 41%. This fascinating difference truly illustrates a contrast in not only real-life communication but in personal approaches to termination. Further into our survey, we presented our participants with several example scenarios, two regarding in-person breakups and two regarding digital breakups. We asked them how they would react in that situation. Our short-term, in-person breakup scenario interestingly presented data contradicting our overarching argument. Here, we found that 29% (5 men) of male respondents would console their partner while 47% (8 men) would present neutral and indifferent body language. On the other hand, only 5 women also reported that they would console their partner, while an overwhelming 11 women said they would be neutral and indifferent. This goes against what we believed – illustrating that the men are more emotionally comforting when it comes to short term relationship termination. It is notable, however, that more men (4) reported showing discomfort in the scenario while only 2 women reported the same. When it comes to long term relationship termination in person, results differ as we had expected. Females showed the highest amount of consoling body language (16 women), while only 12 men reported the same. Men reported being neutral and different more frequently at 3 individuals, yet only 1 woman said the same. Such results are consistent with the findings of an article titled Language and Power in Politics. The article presents a graph which illustrates gender communicative structures – where women are typically empathetic, use emotional references, and use softened statements (Thomas et al., 2019). Men, on the other hand, tend to display solutions, use accusatory speech, and be angry (Thomas et al., 2019). Our results are consistent with these findings – and we can see that, overall, women tend to be more emotionally expressive on the basis of empathy and care than men.

Discussion and conclusions

Exposing levels of emotional expressivity and styles of communication when parting ways can reveal a lot about the way society has influenced us, especially in the way we succumb to traditional gender norms and stereotypes. A higher percentage of women self-reported that they would have open body language and console their partner regardless of relationship length, correlating to the higher levels of males self-reporting emotional restraint in past breakups. Displaying these patterns in extent of closure and vulnerability, both in real-life experiences from prior relationships and predicting behavior in future ones, can reveal how connected gender is to the degree of emotion presented in time of conflict.  In connection to a larger phenomenon, particularly gender norms, men are stereotypically perceived as more indirect, cold, and distant in conflict. In contrast, women are often classified as more elaborate, empathetic, and detailed. After analyzing the data, it appears to mirror underlying notions of masculinity among men as they demonstrated much higher levels of emotional restraint. This not only influences the nature of the relationship itself, but also the ways in which women and men begin to reinforce distinct emotional languages as a result of gendered expectations. After investigating the impact of social conditioning in conforming to gender stereotypes when parting ways, it is important to encourage healthier methods of termination that speak more closely to the identity and desire of the individual rather than to obey the norms that police them.

Cross-References: Watch this to uncover hear about 5 differences in communication between men and women: https://www.youtube.com/watch?v=udAah5Lgx6o

This clip can provide guidance on closure after a breakup:

References

Cinardo, J. (2011). Male and Female differences in communicating conflict (Honors thesis, Coastal Carolina University). Digital Commons at Coastal Carolina University.

Hamlin, E. (2018). Gender and Conflict in Long-Term Romantic Relationships. Stars, 23-35. https://stars.library.ucf.edu/cgi/viewcontent.cgi?article=7045&context=etd

Ogolsky, B. G., Dobson, K., Rivas‐Koehl, M., Kawas, G., & Hardesty, J. L. (2025). The progression of college student romantic relationship development: Stability and change over 10 years. Personal Relationships: Journal of the International Association for Relationship Research. https://doi.org/10.1111/pere.12590

Thomas, S., Greene, E., Brewer, C., Dela Cruz, J. (2019). Language and Power in Politics: A Gender Stereotype Game. Languaged Life. https://languagedlife.ucla.edu/language-and-identity/language-and-power-in-politics-a-gender-stereotype-game/

Ubando, M. (2016). Gender differences in intimacy, emotional expressivity, and relationship satisfaction. Pepperdine Journal of Communication Research, 4(1), Article 13. https://digitalcommons.pepperdine.edu/pjcr/vol4/iss1/13

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Ahmani Guichard, Presley Liu, Isabella Rivera, Dru Stinson

“Hi! Welcome back to my channel,” the YouTuber begins, waving to the camera. She leans back and starts to talk about her day. Ten minutes pass. “Don’t forget to give this video a big thumbs up!” she grins, flashing raised thumbs. The vlog ends. In the polished, highly edited world of YouTube, each movement counts. Like aesthetically pleasing thumbnails and attention-grabbing titles, gestures can be intentional signals online. Whether taking viewers through “A Day in the Life” or “Landing an Internship,” these creators adjust their hands, faces, and posture due to context. This research highlights gestures across casual and serious content while exploring their influence on digital identity. Analyzing clips from publicly available videos/vlogs, the study examines seven categories of gestures: illustrators, emblems, adaptors, posture, hand openness, and head movement. The research dissects how undergraduate female YouTubers convey expressiveness through their nonverbal behavior. The results indicate that casual videos tend to feature more animated, spontaneous gestures. In contrast, those same creators are more composed, employing fewer gestures overall in formal content. By focusing on gestures, this research adds a new dimension to the sociolinguistic understanding of impression management and gendered norms in the digital realm.

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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)

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

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Charlie Kratus, Julian Stassi, Evan Ludwig, Peter Tevonyan, Connor Dullinger

Starting college can be an exciting, but also an overwhelming time, especially when it comes to making friends. However, for many students, sharing their identity starts long before classes begin.

Ahead of setting foot on campus as Bruins, UCLA’s Class of 2029 is already creating their college identity online through Instagram. Newly admitted students post photos as well as a self-created caption. These short bios may seem insignificant, but they actually reveal a lot about themselves. They’re filled with a plethora of different slang, lowercase letters, and emojis.

We wanted to look into how students use different types of language and slang to present themselves. We also observed whether patterns are connected to gender, major, location, or interest in Greek life. We saw clear gender-based patterns where women generally used more informal language. They were much more likely to include emojis, write in lowercase, and use slang than men. Those who identified as male tended to stick to more traditional grammar and formatting. We found that language isn’t just how students talk, it’s how they show who they are and where they fit in among different communities.

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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/

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