Introduction and Background

Drag queens are widely celebrated for their visual artistry, but here we want to demonstrate that some of their most powerful tools are actually linguistic. Through wit, playful insults, and references to iconic celebrities and pop culture moments, drag performers manipulate language in highly creative and entertaining ways. 

Drag performance has long been closely associated with camp, a queer aesthetic and discursive style characterized by irony, exaggeration, theatricality, and the subversion of gender stereotypes and heteronormativity. In an early and pioneering discussion of camp, the theorist Susan Sontag emphasized its stylized appreciation of artifice and exaggeration (Sontag, 1964). While Sontag famously described camp as a sensibility that transforms seriousness into playfulness, later scholars like Jeremy Carl Kelley (2013) have argued that camp should be understood not simply as an aesthetic but as a systematic interactional resource used to construct queer identity and community. 

Linguistic anthropologists have also examined the relationship between drag performance and language. Rusty Barrett’s work on gay male subcultures demonstrates how drag queens use stylized speech practices to construct gendered personas and index community membership (Barrett, 1999). Barrett shows that drag performers frequently shift between multiple speech styles, layering voices and identities in ways that challenge conventional assumptions about gender and language.

For any interested readers, a well-known portrayal of earlier drag and ballroom culture can be seen in the documentary Paris Is Burning, which provides historical insight into the performance traditions that shaped contemporary drag culture (see the trailer here: https://www.youtube.com/watch?v=9SqvD1-0odY )

One of the most visible contemporary spaces where these practices occur today though, is the television show RuPaul’s Drag Race. Since its debut in 2009, the show has become one of the most influential platforms for drag culture worldwide. It functions not only as a competition show, but also as a cultural space where drag discourse and the camp aesthetics that shape it are performed, circulated, and reproduced for both queer communities and mainstream audiences.

This project builds on these insights by asking the following question:

How is camp indexed through language in a highly ritualized performance context such as RuPaul’s Drag Race, and how does this linguistic performance affirm queer identity and culture?

Methods

To explore this question, our project focuses on the popular “Snatch Game” challenge from RuPaul’s Drag Race. In Snatch Game, contestants impersonate celebrities within a parody game-show format inspired by the classic television show Match Game. Unlike other challenges on the show, Snatch Game is all about wordplay: success often depends heavily on improvisational humor, quick wit, and creative cultural references.

Because this analysis examines drag discourse within a televised competition, it is important to situate the speech events within their broader communicative context. Linguistic anthropologist Dell Hymes proposed the SPEAKING model as a framework for analyzing speech events within their cultural settings (Hymes, 1974). The model highlights how communicative practices are shaped by elements such as participants, setting, norms of interaction, and genre.

Snatch Game represents a very layered communicative environment. The setting is a parody game show embedded within a reality competition television series. The participants include the queens performing celebrity impersonations, the host RuPaul, fellow competitors, the in-game “contestestants”, and the broader television audience. The genre blends improvisational comedy, celebrity impersonation, and drag performance.

These overlapping contexts create a form of layered artifice, where contestants perform multiple identities simultaneously: they perform their drag queen personas, impersonate celebrity figures, and compete as contestants within a reality television format. This complex performance structure makes Snatch Game an especially productive site for examining how camp is linguistically constructed and interpreted in a mediated performance setting. 

For this study, eight iconic Snatch Game performances were selected from across multiple seasons of RuPaul’s Drag Race. These performances were chosen as a representative sample  due to their high status within the show’s fan community, illustrating how effectively Ru Paul’s Drag Race disseminates drag performance across the wider culture. Readers unfamiliar with the format can view examples of Snatch Game performances in widely circulated clips online (see this compilation: https://www.youtube.com/watch?v=hRm0WKPyC9M ) 

The selected performances were transcribed and analyzed for recurring linguistic patterns.

Results

The analysis revealed four linguistic strategies that appeared consistently across the selected Snatch Game performances.

Table 1. Linguistic resources used to index camp in Snatch Game performances

Linguistic Resource	Description	Function in Camp Performance
Metapragmatic Humor	Jokes that comment on the performance, situation, or the interaction itself	Highlights the artificiality of performance, generates humor
Intertextual Referencing	References to celebrities, films, music, or cultural icons	Activates shared cultural knowledge and signals queer cultural literacy
Sexual Innuendo	Double entendre and playful or absurd references to sexuality	Produces humor through exaggeration and challenges normative expectations
Character Recognition and Subversion	Establishing a recognizable celebrity persona and then exaggerating or distorting it	Creates camp through parody, exaggeration, and reinterpretation of cultural figures

Table 1: Summary of the four linguistic resources identified in the analysis of Snatch Game performances.

These discursive resources allow drag queens to create camp performances that rely simultaneously on humor, cultural recognition, and exaggerated character portrayal. The following are textual examples drawn from the segments we transcribed.

Metapragmatic Humor: Ginger Minj as Adele, Season 7 Episode 7

Ru Paul: It’s a good answer but not a match darling 

Adele: Well could I get a match please, its a fake cigarette 

Intertextual Referencing: Gigi Goode as Maria the Robot, Season 12 Episode 6 

Ru Paul: Now Maria, do you know Siri and Alexa? 

Maria: One second… searching… she’s my sister, bitch

Sexual Innuendo: Bonnie Ann Clyde as “Chair” (Cher), UK Season 4 Episode 7

Ru Paul: Oh yes, and what a solo act you are, I sit on you all the time

Chair: Sit on someone else’s face, I’m busy! 

Character Recognition and Subversion: Jimbo as Shirley Temple, All-Stars Season 8, Episode 4 

Bowen Yang: Snatchlerette number 4, what song would you say best describes your love life, and why? 

Shirley: I would say “The Good Lollipop” cause I’m a sweet trip to the candy shop! I’m all growed up now, I’m one hundred years old! 

Discussion and Conclusion

When taken together, these findings suggest that camp in drag performance is not only a visual aesthetic or comedic style. It is also indexed through a complex set of linguistic practices that allows performers to manipulate voice, reference shared cultural knowledge, and exaggerate familiar identities to humorous effect. 

Ultimately these linguistic strategies do more than just entertain the audience or advance the queens through the competition. They also function as a way of affirming queer identity and community belonging. In recognizing the references, jokes, and exaggerated performances, the queens draw on a shared cultural repertoire, one that draws on decades of queer history, celebrity iconography, and drag traditions.

In this sense, camp functions as a cultural as well as linguistic resource. Through humor, parody, and exaggeration, drag queens create moments of shared recognition that reinforce a sense of community among audiences and performers alike.

By examining the language of drag performance, this project highlights the important role that linguistic creativity plays in shaping contemporary queer culture. More broadly, it demonstrates how camp continues to function as a vibrant and affirming mode of queer cultural expression.

References

Barrett, R. (1999). From drag queens to leathermen: Language, gender, and gay male subcultures. In M. Bucholtz, A. Liang, & L. Sutton (Eds.), Reinventing identities: The gendered self in discourse (pp. 313–331). Oxford University Press.

Hymes, D. (1974). Foundations in sociolinguistics: An ethnographic approach. University of Pennsylvania Press.

Kelley, J. C. (2013). Queering conversation: An ethnographic exploration of the functional properties of camp-based language use in U.S. gay men’s interactions. UCLA.

Natacha Marjanovic, “Be Proud, and Loud”: Linguistic Markers of Pride in Drag Queens’     Spoken Discourse », Discours [En ligne], 32 | 2023, mis en ligne le 22 juin 2023, consulté le 13 février 2026. URL : http://journals.openedition.org/discours/12425 ; DOI : https://doi.org/10.4000/discours.12425

Sontag, S. (1964). Notes on camp. Partisan Review, 31(4), 515–530.

Natacha Marjanovic, “Be Proud, and Loud”: Linguistic Markers of Pride in Drag Queens’ Spoken Discourse », Discours [En ligne], 32 | 2023, mis en ligne le 22 juin 2023, consulté le 13 février 2026. URL : http://journals.openedition.org/discours/12425 ; DOI : https://doi.org/10.4000/discours.12425

Appendix

Snatch Game, Ru Paul’s Drag Race, Select Transcriptions 

Bonnie Ann Clyde as “Chair”, UK Season 4 Episode 7 

Ru: Up next (.) <take a seat y’all>it is chair (cheering)

Chair: Hey R::u (.) it’s been so long (.)  you might not recognize me since I’ve been reupholstered so many <times>

Ru: [hhh- 

Chair: [You wanna know what they’re starting to call it? 

Ru: What?

Chair: A [chairlift

Ru: [hhh (.) now chair, do you get along (.) with the other furniture in the living room?

Chair: I d::o, I used to be in a relationship with one of them actually we were called table and chair

Ru: [hhh 

Chair: [so

Ru:[hh

Chair: [it didn’t work out so I’m a s::olo act n::ow

Ru: Oh and what a solo act <you are> (.) I sit on you ::all the time 

Chair: Sit on someone else’s face I’m busy

Ru:hhh

Ginger Minj as Adele, Season 7 Episode 7

Ru: Last but not least, music superstar Adele is here

Adele: Could I buy a vowel? 

Ru: What is that darling?

Adele: No emmys! 

Ru: No no no this is the wrong show!

Adele: Okay 

Ru Paul: Where in England are you from Adele? 

Adele: My house 

Ru Paul: Alright, now Dorothy blanks the Tin Man

Adele: Well if it was me, I would say she rips out his heart and then sings a whole album about it, and gets really popular but its not me

Ru Paul: No, no 

Adele: So I said, she polishes his chrome 

Ru: It’s a good answer but not a match darling 

Adele: Well could I get a match please, its a fake cigarette 

Gigi Goode as Maria the Robot, Season 12 Episode 6 

Ru Paul: Hi Maria 

Maria: What’s up, bitch? 

Ru Paul: Now, do you know Siri and Alexa? 

Maria: One second, searching, she’s my sister, bitch 

Jujubee as Eartha Kitt, Season 5 Episode 4

Participant: Contestant number two, I’m originally from Canada, so if we went up there for a winter visit, how would you keep me warm? 

Eartha: I would sensually walk to the thermostat, and turn up the thermostat to a sensible seventy four.

Participant: Contestant number two, same question

Eartha: Ribbet, ribbet, I am a lady frog, and you are a sweet prince, and I am convincing you 

Jinkx Monsoon as Little Edie (Gray Gardens) Season 5, Episode 5 

Ru Paul: Direct fro Grey Gardens its little Edie Beale

Edie: Oh hi Ru 

Ru Paul: How is big Edie doing

Edie: She’s always begging for the paté, but the label is faded, I can never tell if its paté or if its jiblets for the cats 

Edie: Ru, if I might ask you, why you couldn’t have gotten any real celebrities for this game? 

Ru: Well

Edie: I don’t have a single idea who any of these people are, you could’ve gotten Leslie Careoux or Audrey Hepburn or any one of them and instead you got Ketchup? 

Kesha: Ketchup? 

Edie: And that must be Janice Jickson? 

Alexis Michelle as Liza Minelli, Season 9 Episode 6

Ru Paul: Ring them bells, it’s Liza Minelli, or is it Lisa Minulli? 

Liza: No Ru, its Liza, with a Z, it has a Z

Ru: Its Liza with a Z

Liza: WIth a Z!

Ru Paul: Liza Minelli

Liza: I said, Ladybunny’s Palace, 

Ru Paul: Her palace 

Liza: Because, there’s nothing like playing the palace,

Ru Paul:[hhhh

Liza:  Mama played the palace, and I sat right in the fourth row

Ru Paul:[wow

Liza:[She sang right to me

Ru Paul:[Oh boy

Liza: And to all the other homosexuals 

Ru Paul:[hhhh

Ben De La Creme as Maggie Smith, Season 6 Episode 5 

Ru: Alright, Dame Maggie Smith, Cher, completely addicted to social media, even her blank has a twitter account. 

Maggie: Well, ruple, Ruple is it? I understand virtually none of the words that left your lips moments ago, but I did hear the term twitter and I assumed that it’s some sort of a songbird? 

Ru:[hhh Very close, not a match…

Maggie: Am I to understand that one yanks one’s telephone right out of the wall and carries it with him? 

Ru: Yes 

Ru (to Nicki): You didn’t write down anything? 

Nick: No

Maggie: Perhaps she needs another pot of ink to replenish her quill 

Ru: Let’s move on down to Dame Maggie Smith

Maggie:[Well I’m unfamiliar with the work of lady Handler, however I did think that it would be rather amusing if there were libation flavored with…citrus hhh

Ru:[hhhh

Maggie: Can you imagine such a thing 

Ru:[hhh that is really newfangled I can’t imagine such a thing 

Jimbo as Shirley Temple, All-Stars Season 8, Episode 4 

Ru: She’s America’s OG sweetheart, Shirley Temple is here

Shirley: Well hello Ru! 

Ru:[hhhh

Shirley: I won the hearts of America and the world 

Ru:[hhhh yes you did, are you ready to win the heart of a nice “snatchler”?

Shirley: I don’t know, does he know how to babysit?

Ru:[hhhh

Bowen Yang: Snatchlerette number 4, what song would you say best describes your love life, and why? 

Shirley: I would say “the good lollipop” cause I’m a sweet trip to the candy shop

Ru:[hhhhh 

Shirley: I’m all growed up now, I’m one hundred years old

Oyna Nurve as Eddie Murphy, Season 17 Episode 7 

Ru: Up next, comedy superstar, Eddie Murphy is here

Eddie: I’m so excited for tonight’s episode of the Snatch Game woo

Ru: Eddie, which is your favorite Greek superstar?

Eddie: You know its Hercules, Herecules, Hercules, Hercules, Hercules

Ru:[hhhh

Eddie:[hhh oh my mustache almost fell off

Introduction and Background

In recent years, online platforms have witnessed the rise of “brain rot” meme culture, characterized by a highly compressed and playful form of English. Featuring neologisms such as rizz and sigma, this emerging digital dialect—closely associated with Generation Alpha—is shaped by TikTok, YouTube, and gaming communities. Its emergence has generated generational tension, as older speakers often dismiss it as degraded or non-academic, reflecting a broader tendency to devalue unfamiliar forms and overlook the ongoing reinvention of English in a digitalized world (Rachmijati & Cahyati, 2024).

While digital communication highlights the adaptability of English, such forms are not equally appropriate across contexts. As younger speakers become increasingly fluent in Generation Alpha slang, questions arise about their ability to shift into formal academic registers. Conversely, Millennials often struggle to interpret the highly contextual, multimodal discourse of online platforms. To examine this register mismatch, our study focuses on Generation Alpha (2010–2024) and Millennials (1981–1996) (Springtide Research Institute, 2025).

Here, we intend to focus our research on how these two groups perceive linguistic features such as simplified syntactic structure, acronyms, and digital-specific discourse, particularly investigating how they are interpreted in everyday digital communication, and then reformulated within the academic context. Utilizing the previous data classifications conducted by Tilagavati Subramaniam & Muthualagan Thangavelu in the Journal “Exploring The Use of Digitalised Slang in Verbal Communication Among Generation Alpha” data and word meaning shown in Table A.1 Gen Alpha Slang and Definition for reference.

Therefore, we ask, “How has the rise in smartphone usage and digital media consumption, specifically in the form of online humor and digitally-mediated slang, contributed to an overall register mismatch between digital language and academic English language across Generation Alpha adolescents and Millennials?” This question ultimately seeks to determine whether individuals who are fluent in interpreting these highly contextual forms of digital language are equally able to reformulate them within the formal language expected in academic writing.

Methods

We collected data through an online questionnaire distributed to seven participants from both Generation Alpha and Millennial groups. The survey examined both participants’ exposure to digital language and their ability to interpret and reformulate it. Participants first reported their daily screen time and most frequently used platforms. They then completed interpretation tasks based on real examples of online discourse (e.g., “I’m dead,” “too real”), where they expanded comments from an Instagram reel to explain their meaning in context. In addition, participants interpreted a meme involving layered cultural references.

Finally, participants completed reformulation tasks, rewriting slang-based expressions (e.g., “main character energy,” “clout chasing”) into formal academic language. Responses were analyzed by comparing interpretive competence (ability to explain meaning and context) and linguistic competence (ability to produce structured academic language), with attention to patterns across generational groups.

Results and Analysis

All participants reported high levels of digital exposure, with four to nine hours of daily screen time and frequent use of TikTok and Instagram. Both groups were familiar with widely circulated slang such as “rizz,” “slay,” and “no cap,” yet this shared exposure did not translate into similar communicative competence.

When shown the reel, interpreted by the contrasting attitudes of an Asian father before and after his child’s success, Generation Alpha consistently demonstrated strong interpretive ability. When explaining expressions such as “I’m dead,” they produced context-rich paraphrases (e.g., “it means something is so funny that you can’t react normally”), and for “too real,” they referenced shared social experiences (“parents likes telling others what to do”). In the meme task, Gen Alpha participants explicitly recognized intertextuality; one described the meme as “a bunch of brain-rot text where each word references another meme,” showing awareness that meaning emerges from accumulated cultural references rather than sentence-level semantics.

Table B.1 Gen Alpha Slang and Definition

Slang	Meaning
1.Skibidi	Nonsense
2.Sigma	Independent
3.Gigachad	Hyper-masculine ideal
4.Gyatt	Admiration
5.Yeet	Exclamation of excitement
6. Slay	To do something exceptionally well
7.Delulu	Delusional
8. Its Giving	Something Aesthetic
9.Cap	Lie
10. No Cap	No Lie or Truth
11.Vibe	The atmosphere
12.W	Success
13.Tea	Gossiping
14.Fanum Tax	Stealing Something
15.Ate	Awesome
16.Cloud 9	Happy
17.Feeling Blue	Sad
18.Sus	Suspicious
19.Bruh	Addressing someone boy or girl
20.Ohio	Awkward
21.Rizz	Ability to flirt or attract others
22.Drip	Stylish
24.Idk	I don’t know
25.Cook	Doing really well at something
26.Snatched	Looking amazing
27.Bet	Okay
28.Flex	Show
29.Yassify	Exaggerated Beauty
Note:Table B.1 Gen Alpha Slang and Definition referenced Ishita & Radhika Mamidi’s study and compilation 100 slang words and definitions from Gen  Alpha research subject Source: Cited from “Exploring The Use of  Digitalised Slang in Verbal Communication Among Generation Alpha” by Tilagavati Subramaniam & Muthualagan Thangavelu.

This pattern is even more evident in the meme task. One Gen Alpha participant described the meme as consisting of “a bunch of brain-rot text… each word is a callback to another meme,” demonstrating awareness of intertextual meaning. Understanding such content requires familiarity with broader cultural references rather than sentence-level logic.

These differences became more pronounced in reformulation tasks. Gen Alpha participants were generally able to grasp the meaning but struggled to expand it into formal academic language; for example, “main character energy” was reduced to “confidence,” and “clout chasing” to “seeking attention,” omitting evaluative and social nuance. Millennials, however, often struggled at both stages: some failed to interpret phrases like “The function was totally Ohio but the fit was a massive W,” recognizing “W” as success but expressing confusion about “Ohio,” which relies on meme-specific context.

Taken together, these results suggest a distinction between interpretive competence and linguistic competence. Participants are often able to understand digital language but vary in their ability to translate it into formal academic expression.

Discussion and Conclusions

These findings suggest that the gap between digital and academic language reflects differences in how meaning is structured, rather than differences in overall ability. Digital discourse often compresses complex meanings—such as identity, humor, and social evaluation—into short, context-dependent expressions. Academic language, by contrast, requires these meanings to be made explicit and fully articulated. Moving between these systems therefore requires different communicative skills.Generational differences further highlight this divide. 

Generation Alpha participants showed strong interpretive competence, particularly in reconstructing context and understanding implicit meaning. Millennial participants, on the other hand, were more comfortable producing structured academic language but sometimes lacked familiarity with digital cultural references. Rather than indicating a decline in language ability, these patterns point to the coexistence of two distinct but overlapping literacy systems. The observed register mismatch emerges not because one group is less capable, but because different forms of competence are developed in different communicative environments.

Works Cited

Rachmijati, C., & Cahyati, S. S. (2024). Know your skibidi: Navigating Gen Alpha’s slang types and trend on social media X. Proceeding of the 4th International Conference on Research and Development (ICORAD), 3(2), 392–400. https://doi.org/10.47841/icorad.v3i2.219

Springtide. (2025, May 20). New Data From Our Study on Gen Alpha. Springtide Research Institute. https://springtideresearch.org/thirteen-a-first-look-at-gen-alpha.

Subramaniam, T., & Thangavelu, M. (2025). Exploring The Use of Digitalised Slang in Verbal Communication Among Generation Alpha. Journal of Cultural Analysis and Social Change, 10(3), 236–243. https://doi.org/10.64753/jcasc.v10i3.2401

Introduction & Background

Anyone who has watched the same movie in two different languages has probably noticed that the dialogue does not always translate directly. Animated movies, in particular, are landmines for translators. They frequently rely on culture-bound references: nursery rhymes, idioms, historical events, or well-known characters that the original audience is just expected to recognize. In the original English context, these references can enrich a scene by adding layered humor and shared cultural knowledge.

However, when films are dubbed, these elements hit a massive barrier. Translators working in audiovisual media aren’t just swapping English words for their direct Polish or Japanese counterparts; they must make critical, culturally loaded decisions. Should they preserve the original reference and risk confusing the audience? Adapt it to something local and familiar? Or remove it entirely?

These choices mean that translation is never a word-for-word transfer. It is an active cultural process that shapes how global audiences understand the same film. While previous research shows that Arabic dubbing navigates complex dialect choices to build emotional connection (Al-Yasin, 2022), Polish dubbing domesticates references (Leszczyńska & Szarkowska), and Japanese translations often engage in “cultural deodorization” to soften foreign elements (Hyland, 2015), there is still a gap in understanding how major dubbing studios systemically navigate these choices across vastly different linguistic contexts side-by-side.

This project explores how translators adapt these references across Polish, Arabic, and Japanese, and how these decisions reflect specific sociocultural expectations.

Methods: Decoding the Dubs

To figure out how studios handle this, we didn’t just re-watch our childhood favorites; we conducted a qualitative comparative analysis. We zeroed in on culturally dense scenes from Shrek, Shrek 2, Toy Story, Aladdin, Monsters Inc., and Finding Nemo.

We defined a “culture-bound reference” as any element relying on shared knowledge for its meaning or humor (like a specific food, idiom, or pop-culture nod). We then aligned the original English dialogue with its Polish, Arabic, and Japanese dubbed versions.

To make sense of the changes, we coded every translated line using Davies’ (2003) translation strategies framework. The main categories we look at were:

• Preservation: keeping the original reference

• Localization: replacing it with a culturally familiar equivalent

• Globalization: using a more general or neutral term

• Transformation: significantly altering the meaning or structure

• Omission: removing the reference entirely

Coding was conducted by comparing the original line with its dubbed versions and identifying how the cultural reference was handled. In cases where multiple strategies appeared in a single line, the dominant strategy based on the most significant shift in meaning was selected.

While the analysis focuses on linguistic changes, it also takes into account key constraints of audiovisual translation, such as lip synchrony and timing, which can limit how closely dialogue can match the original. This allowed us to interpret translation choices not only as linguistic decisions, but as responses to both technical and cultural pressures.

Results & Analysis: Who Changed the Joke?

When coded using Davies’ framework, the data revealed different adaptation strategies across the three languages.

Table 1: Frequency of adaptation strategies for culture-bound references in Polish, Arabic, and Japanese dubs of English animated films, categorized using Davies’ (2003) framework. The data shows Polish favoring Transformation/Localization, while Japanese favors Transformation/Omission

The patterns suggest that Polish dubbing prioritizes cultural substitution, where the goal is not to preserve the original reference itself, but to recreate its effect for the audience. Rather than expecting viewers to interpret unfamiliar references, translators replace them with culturally accessible equivalents that allow the humor to land immediately. This reflects an underlying assumption that shared cultural knowledge is essential for comedic impact.

Arabic dubbing shows a broader mix of strategies. This flexibility reflects the incredible linguistic and cultural diversity of Arabic-speaking audiences. In some cases, translators localize references, such as replacing “muffin” with ka’k, a well-known Middle Eastern baked good. In other cases, references are simplified through globalization, such as translating “white bronco” as “white horse.”

We found that Arabic dubbing balances between cultural familiarity and broad accessibility. Because dubbed media often targets a wide, transnational audience, translators may avoid highly localized substitutions that would only resonate in one region. Instead, they favor solutions that are widely understandable across dialects and cultural contexts, prioritizing clarity over introducing specific cultural references.

Japanese dubbing tends to rely on transformation or omission, often removing references that don’t translate culturally. For instance, the nursery rhyme reference to the “Muffin Man” is omitted entirely and replaced with a more neutral line self-referencing the speaker as the “Cookie Man”.

Clear favoring of transformation and omission in Japanese dubbing suggests a preference for maintaining clear narrative flow and cultural neutrality rather than confusing the audience with unfamiliar Western concepts. This also aligns with a broader tendency to minimize overt foreignness, allowing the story to feel more cohesive even if some cultural detail is lost.

To see this in action let’s look at the famous interrogation scene in Shrek.

Table 2: Adaptation of the “Muffin Man” nursery rhyme reference in Shrek. This highlights how a single joke fractures into three entirely different linguistic strategies based on cultural expectations.

Disscusion

Our findings confirm that language in animated films is deeply tied to culture. Rather than acting as a direct transfer of meaning, dubbing functions as an active form of cultural adaptation. As Johnson (2020) argues, dubbing exists in a space “between” languages and cultures, where meaning is actively reconstructed to fit new contexts. This helps explain why the same film can feel subtly different depending on the language in which it is viewed.

The patterns observed aren’t just random choices made by translators in a booth; they reflect broader language ideologies about what audiences should understand and how much “foreignness” is acceptable in media. These translation choices affect indexical meaning- the social and cultural associations carried by language. Culture-bound references like the Muffin Man do more than just push the plot forward; they signal shared knowledge, history, and identity. When translators replace or erase those references, the indexical meanings shift, fundamentally altering how audiences engage with the characters on screen.

Ultimately, global media is not experienced uniformly. What may seem like a tiny change to a joke about a muffin actually reveals a much larger, ongoing process of cultural negotiation. The next time you watch a dubbed film, pay close attention to the jokes- you might be surprised by what you’re actually laughing at.

References

Al-Yasin, N. (2022). Translation Procedures of Cultural-Bound Expressions in the Egyptian Vernacular Dubbed Versions of Three Disney Animated Movies. Open Cultural Studies, 6(1), 294-306.

Burczyńska, P. (2012). Translation of cultural items in dubbed animated comedies. Translation Journal.

Di Giovanni, E. (2016). Dubbing and redubbing animation: Disney in the Arab world. Altre Modernità.

Huber, L., & Kairys, A. (2021). Culture Specific Items in Audiovisual Translation: Issues of Synchrony and Cultural Equivalence in the Lithuanian Dub of “Shrek the Third.” Kalbų Studijos, 1(38), 5-16.

Hyland, R. (2015). A culture of borrowing: Iconography, ideology and idiom in Kari-gurashi no Arietti/The Secret World of Arrietty. East Asian Journal of Popular Culture, 1(2), 205-222.

Leszczyńska, U., & Szarkowska, A. (2018). “I don’t understand, but it makes me laugh”: Domestication in contemporary Polish dubbing. The Journal of Specialised Translation, (30), 203-221.

Rababah, L. M. (2025). Cultural challenges and subtitling strategies in American animated movies. Journal of Posthumanism, 5(2).

Some Info and Context 

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

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

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

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

What Did We Decide To Do?

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

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

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

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

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

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

So, What Did We Find?

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

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

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

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

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

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

Food For Thought

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

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

Bibliography

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

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

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

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

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

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

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

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

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

Introduction

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

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

Background

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

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

Methods

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

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

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

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

Findings

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

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

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

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

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

Impact

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

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

References

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

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

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

Introduction

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

Methods

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

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

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

Results

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

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

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

Conclusions

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

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

Refrences

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

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

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

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

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

Introduction 

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

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

Methods

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

Results

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

Figure 1

Number of Participants by Age Range

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

Firgure 2

Distribution of participants by workplace setting.

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

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

Figure 3

Average perceived professionalism of informal linguistic features.

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

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

Conclusion

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

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

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

References

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

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

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

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