Remixing Stereotypes: How Gendered Scripts Evolve Through TikTok’s Viral Culture

Abstract

This study investigates how gender stereotypes are performed and transformed through viral TikTok trends. While prior research has documented the persistence of gender norms in traditional media, less is known about how they circulate in participatory digital platforms driven by algorithmic visibility. Using a qualitative content analysis of 150 viral TikTok videos across 15 gender-related trends (2023–2025), this project examined both behavioral scripts and identity labels—formats that exaggerate gendered behavior or crystallize personality types. Each post was coded for tone, creator gender, and orientation toward stereotypes, with audience engagement analyzed through comment sections.

Findings reveal four recurring patterns: exaggerated performance, ironic reinforcement, gendered authenticity, and audience co-production of meaning. Together, these show that TikTok functions not as a passive mirror of gender norms but as a participatory system that constantly remixes them. The study contributes to ongoing debates about humor, irony, and digital performance, showing how participatory media both challenge and sustain cultural stereotypes.

Introduction

On TikTok, small jokes can turn into shared language overnight. A creator jokes, “She’s a 10 but keeps five-minute voice memos for every minor inconvenience,” and thousands reply with their own versions. Another sound—“I’m just a girl”—sets off a wave of videos performing femininity with a wink, while the comments debate whether it’s satire or self-own. These aren’t just jokes; they’re the raw material for how people talk about gender.

TikTok has become one of the most powerful cultural stages of our time. Trends that begin as small jokes or offhand performances can spread to millions of people within days, repeating until they feel woven into everyday language. These trends don’t just spread quickly; they invent new ways of talking. Many lean on gender, packaging familiar stereotypes in new forms or inventing fresh labels that quickly spill outside the app and into everyday speech. These labels, along with repeated jokes about behavior, act as a script for how we see one another. What starts as humor begins to shape how people describe each other, how they understand themselves, and how gender is talked about in the culture at large.

This project asks: How do gender stereotypes appear in TikTok’s most viral trends, and what patterns emerge in how they are reinforced, challenged, or redefined across genders? Some of these patterns show up as recurring behaviors—repeated jokes about actions tied to gender. Others take shape as labels or characters, shaping how people talk about each other offline. Both matter. The behaviors show how everyday actions are framed through gender expectations, while labels and characters harden into recognizable identities that can stick to people in everyday conversation.

Key terms. In this paper, scripts refer to repeatable formats that exaggerate behavior (such as jokes or skits), while labels describe shorthand identities like “pick-me girl” or “sigma male.” Both circulate through trends; TikTok’s viral formats are built around shared sounds, captions, or hashtags. Together, they show how the platform transforms gender norms into repeatable and remixable content.

The research design gathered a set of TikTok’s most viral, gender-related trends and analyzed them collectively. By examining both the scripts that exaggerate everyday behaviors and the labels that solidify into identities, the project traced the gendered messages these trends convey, who produces them, and how they shift when applied to mixed-gender contexts. From this analysis, four main patterns emerged: exaggerated performance, ironic reinforcement, gendered authenticity, and audience co-production of meaning. Each reveals something distinct about how gender circulates through TikTok’s participatory culture. 

Exaggerated performance refers to the way creators dramatize gendered behaviors until they become caricatured. These performances make stereotypes visible but also contribute to their recirculation through repetition.

Ironic reinforcement describes the ambiguity that occurs when a creator mocks a stereotype while simultaneously repeating it. Because irony is difficult to detect on TikTok’s fast-moving feed, satire often looks very similar to sincerity, which allows stereotypes to spread even when users intend to critique them.

Gendered authenticity highlights how creators perform “realness” in different ways depending on gender. Women often express authenticity through openness, confession, or vulnerability, while men typically frame it through logic, control, or self-discipline. These differences show that even authenticity follows gendered scripts.

Audience co-production of meaning captures how comments, stitches, and duets shape the interpretation of a post. Meaning becomes collaborative rather than fixed, and audience participation keeps stereotypes active long after the original video is posted.

Together, they show that gender on TikTok is never static but constantly being performed, reinterpreted, and reshaped through humor and participation. The goal was not just to collect examples, but to see the larger dynamics at work: what fades as a passing joke, what hardens into a stereotype, and what gets flipped into something subversive. By recognizing those dynamics, this study aims to show how humor-driven digital culture shapes how gender is understood and talked about today.

Conceptualizing Gender Stereotypes in Media

The media has long served as one of the most influential sites for shaping how gender is understood. Classic theories of gender stereotyping emphasize how portrayals of men and women become cultural scripts that audiences internalize and reproduce (Eagly et al., 2019). These scripts are rarely neutral. Men are typically framed as decisive, assertive, independent, or unemotional, while women are cast as passive, nurturing, or even decorative (Hentschel et al., 2019). These scripts gain power from repetition. Over time, these portrayals appear natural and normalized, giving the impression that they reflect reality instead of actively shaping it.  

Research confirms that gender stereotypes remain persistent across media forms. Santoniccolo et al. (2023) show that mainstream representations continue to objectify and sexualize women, while Lauzen (2018) documents women’s ongoing underrepresentation both on screen and behind the camera on television. Studies of professional settings also reveal similar processes: job advertisements often contain language that subtly reinforces gendered expectations (Sczesny et al., 2024). Even scientific communication is not exempt from this; Chen (2024) finds that controversial science dialogue online often carries gendered assumptions. Together, these studies demonstrate that stereotypes remain embedded in communication, but that leaves a gap in how they circulate in participatory environments like TikTok, where ordinary users rather than producers drive representation. This project addresses that gap by tracking how gender stereotypes and scripts are recycled or reshaped in viral trends on participatory platforms like TikTok.

Humor, Memes & the Reinforcement of Stereotypes

Humor is one of the most enduring ways stereotypes are transmitted. Jokes that target gender may appear harmless, but they reinforce bias by presenting stereotypes as socially acceptable (Ford & Ferguson, 2004). Memes work similarly: they depend on instant recognition, which often means they repeat familiar gendered tropes (Meghana & Vijaya, 2020). Recent studies confirm that sexist memes can influence emotional and moral processing, making discriminative attitudes seem less problematic (Paciello et al., 2021). These findings show that humor and memes play a serious role in stabilizing gender norms. 

At the same time, humor has the potential to destabilize stereotypes. Exaggerating gendered behaviors to extremes can expose how unnatural those stereotypes really are.  (Matamoros-Fernandez, 2023) shows how features like duets, stitches, and sound reuse encourage endless remixing of jokes, sometimes reinforcing stereotypes and sometimes tearing them down. Meme analyses by Sultana (2025) and Mihailescu (2024) show that memes can be flipped to question or debate social roles. This tension, between reinforcing and challenging, is significant to TikTok humor, which dominates viral content. This project, therefore, examines not only how jokes reinforce gender stereotypes but also when and how they create cracks.

Digital Labeling in Online Culture

Online culture frequently condenses complex identities into shorthand labels. Nilsson (2024), for instance, documents how the “I’m just a girl” TikTok trend packaged gender performance into a recognizable cultural script, while Tanner (2025) analyzes “sigma male” discourse as a form of toxic communication that reframes masculinity. In both cases, labels crystallize stereotypes while also creating opportunities for new forms of identity work. 

Labels are rarely descriptive alone. They almost always will imply judgment. To be called a “pick-me girl” means being critiqued for seeking male validation, while “sigma male” often mixes parody with aspiration. Huber and Baena (2023) show that women scientists on TikTok sometimes embrace labeling strategies to increase their visibility, though it risks reinforcing old stereotypes about women in STEM. Steinke (2024) expands this, noting that female creators both embrace and resist labels as part of identity work. Yang (2023) conceptualizes this process more broadly, describing memes and labels as “cultural scripts” showing how memes and shorthand terms shape identities online. These examples show how online labeling both simplifies and amplifies identity work. On TikTok, those labels spread even faster because anyone can adopt, parody, or remix them. This project follows that insight by examining how viral TikTok labels work to reinforce, reshape, or challenge stereotypes.  

TikTok’s Amplification of Gendered Trends

What makes TikTok different from earlier forms of media is its speed and its algorithm. Its “For You Page” curates content in ways that don’t just reflect popularity but actively construct it (Varmazyar & Cardama, 2023). Dillon et al. (2023) found TikTok content often reproduces bias, while Yin and Abdullah (2024) found that negative portrayals of women spread quickly through trending content. In other words, stereotypes on TikTok are not just reproduced, but they are accelerated by design. 

At the same time, TikTok’s constant remixing changes how these trends play out. A single sound may generate thousands of versions. some repeating stereotypes, others mocking them. Remixing matters because it’s how meaning gets made on TikTok: each reuse of a sound or caption gives an old idea new life, sometimes as humor, sometimes as critique, and sometimes as both at once. Suarez-Garcia et al. (2024) demonstrate how sexism appears in multimodal video data. Matamoros-Fernandez and Farkas (2023) highlights how humor and amplification interact to make harmful content that becomes both visible and normalized. Yet platforms like TikTok can also enable resistance. Huber and Baena (2023) show how women scientists use TikTok to disrupt expectations and assert their own new forms of visibility. Taken together, this research positions TikTok as both an amplifier and medium for resistance, reflected by their spreading of stereotypes at scale, while also simultaneously offering space for rebuttals. This study builds on that work by examining how gendered scripts and labels circulate in viral trends and whether they are reinforced, parodied, or redefined.  

Data and Methods

TikTok as a Research Site

TikTok has become one of the fastest-growing social media platforms over the past five years, with estimates projecting its global user base to exceed 1.5 billion monthly active users by 2025 (Business of Apps, 2025; Boeker & Urman, 2022). Unlike traditional media, TikTok is participatory, meaning users don’t just consume content; they actively produce and remix it. TikTok’s duet and stitch features, tools that allow users to place their videos alongside or directly after another creator’s post, also make trends highly interactive, enabling users to respond, critique, or extend a trend in ways that shape how gender stereotypes circulate. This makes it a uniquely useful site for studying gender stereotypes. Prior scholarship has shown how stereotypes are embedded in traditional media like television, film, and advertising (Goffman, 1979; Lauzen, 2018), but TikTok provides an opportunity to observe how those scripts spread, change, and gain traction in real time. While TikTok’s algorithm is central to this process, it is not transparent and cannot be studied directly. Instead, this project examines its manifestations: the trends that receive disproportionate visibility and circulate widely on the platform. As a young woman familiar with TikTok culture, I approached this research both as a participant and observer. My interpretations were informed by an understanding of platform humor, but I aimed to stay reflexive about how my own perspective might shape what I noticed. Because TikTok’s algorithm determines visibility in opaque ways, examining trends themselves, rather than trying to access the system behind them, became the most effective way to study how gendered content gains traction on the platform.

Defining and Selecting Trends

On TikTok, a “trend” refers to a repeatable format that thousands of users adapt with their own variations, often built around a shared sound, hashtag, or caption (Ling et al., 2021). In this study, I focus on two types of trends. The first are scripts, which take the form of jokes or skits that exaggerate a behavior. The second are labels, short phrases that mark out an identity or archetype. These trends matter because they reduce gender stereotypes into recognizable forms that can easily be repeated and remixed, ensuring their circulation across diverse audiences. Each reuse or remix of a trend pushes the stereotype further, sometimes reinforcing it and sometimes twisting it into parody or critique (Meghana & Vijaya, 2020).

Sampling Strategy

For this project, I examined viral trends from 2023 to 2025. Because TikTok does not provide a fixed threshold for virality, I developed my own operational definition: a trend counts as “viral” if an individual post reaches at least 100,000 views or 10,000 likes. These thresholds were chosen because they indicate visibility beyond a creator’s immediate follower base and align with prior research that uses engagement ratios as markers of wide circulation (Zhou, 2024).

Trends were identified through two complementary strategies. First, I used an “influencer-first” discovery, beginning with well-known creators across niches. Second, I used trend-first discovery, searching TikTok’s sound pages and hashtag feeds to locate formats gaining traction across multiple creators. To determine whether a trend was spreading beyond a single creator network, I examined whether the same sound or hashtag appeared across diverse accounts, especially when creators were unconnected by follower networks or genre. Using both strategies allowed me to capture trends that spread top down through influencers as well as those that emerged more organically from everyday users.

Dataset and Coding

The dataset included 15 viral trends, each represented by approximately 10 posts, for a total of about 150 posts. These trends reflected both male-coded and female-coded stereotypes. Before selecting videos for analysis, I applied several exclusion criteria: videos in languages other than English, reposts or spam content, advertisements, and posts where either creator’s gender or target gender could not be reasonably inferred. These exclusions helped keep the sample consistent and ensured that all posts could be analyzed using the same categories.

The dataset included 15 viral trends, each represented by approximately 10 posts, totaling around 150 posts. These trends reflected both male-coded and female-coded stereotypes. Each post was logged in a Google Sheet, with one row per video and the following structured fields:

• Trend Name: The viral format or meme category
• URL: The direct link to the post, ensuring retrievability
• Creator Gender: The gender identity that the creator presented in the video or on their profile, recorded as male, female, both (for group accounts), or unclear
• Target Gender: The group toward whom the stereotype, label, or joke was directed, recorded as male, female, both, or unclear
• Tone: The manner in which the stereotype was delivered, categorized as serious, ironic, parody/satire, or ambiguous
• Valence: The overall orientation of the post toward the stereotype, recorded as reinforcing, countering, or mixed
• Notes: A free-text column where I recorded my own observations about each post
  

The “Notes” section included details that did not fit neatly into categories—such as how the creator used captions, body language, or sound; whether the performance exaggerated a stereotype for humor; or if the video seemed to blur critique and reinforcement at the same time. In addition to my own interpretation, I also noted patterns in audience response by scanning top comments and engagement. These reactions provided insight into how viewers were reading the video—whether they laughed along, pushed back, or reinterpreted it. Together, this combination of creator performance and audience reception gave a fuller picture of how gendered trends were being interpreted on TikTok.

Because this project was conducted by a single researcher, no formal inter-rater reliability test was possible. Instead, I used a reflexive coding process to strengthen consistency. After coding the first 30 posts, I revisited my original labels for tone, valence, and target gender, compared them with later entries, and refined the category definitions to reduce ambiguity. I then re-coded a subset of earlier videos using the updated definitions to ensure that my interpretations were stable over time. While this is not a substitute for multi-coder reliability, it provides a structured way to check for consistency in a single-researcher qualitative study.

Table 1. Descriptive Overview

Category	Sub-Category	Count	Percent of Total
Trend Type	Total Viral Trends	15	–
Creator Gender	Female-presenting	75	50.0%
	Male-presenting	45	30.0%
	Unknown / Mixed / Not Obvious	30	20.0%
Tone	Serious	45	30.0%
	Parody / Satire	41	27.3%
	Serious / Playful Blend	10	6.7%
	Other / Hybrid Forms	54	36.0%
Valence	Reinforcing	72	48.0%
	Countering	21	14.0%
	Mixed	57	38.0%

The “hybrid” tone category included videos where creators shifted between sincerity and parody, or where tone could not be cleanly separated because irony and seriousness were blended within the same performance.

Table 2. Overview of the 15 TikTok Trends Included in the Dataset

Trend Name	Type (Script/Label)	Brief Description	Dominant Tone	Primary Target Gender
She’s a 10 but…	Script	Rating game where trivial behaviors affect attractiveness	Parody / Hybrid	Mixed
The Ick	Script	Performances of sudden disgust triggered by small habits	Parody	Male
Pick-Me Girl	Label	Exaggerated portrayal of girls seeking male validation	Satire / Hybrid	Female
Sigma Male	Label	Stoic, lone-wolf masculinity archetype	Serious / Hybrid	Male
High Value Man	Label	Self-improvement masculinity tied to dominance & status	Serious	Male
Looksmaxxing	Label	Optimization routines aimed at increasing physical appeal	Serious / Hybrid	Male
Almond Mom	Label	Critique of diet-focused, controlling maternal behaviors	Satire	Female
Female vs. Male Gaze	Script	Comparing masculine vs. feminine standards of attractiveness	Hybrid	Mixed
Girl Math	Script	Humorous justification of spending habits	Parody	Female
Girl Dinner	Label	Minimalist, snack-based meals framed as a humorous aesthetic	Parody / Satire	Female
I’m Just a Girl	Label/Script	Ironically exaggerated femininity using the No Doubt lyric	Hybrid	Female
Women in Male Fields	Script	Gender minority experiences in male-dominated contexts	Serious / Hybrid	Female
Men in Female Fields	Script	Gender minority experiences in female-dominated contexts	Parody / Hybrid	Male
Performative Male	Script	Parodies of exaggerated masculine behavior	Parody	Male
Trad Wife	Label	Romanticized domestic femininity framed as a lifestyle aesthetic	Serious / Hybrid	Female

Sample of Composition

The final dataset included 150 posts drawn from 15 distinct viral TikTok trends, with around ten posts collected for each. Together, these posts captured how gendered humor, labeling, and performance show up in TikTok’s most visible spaces between 2023 and 2025. As shown in Table 1, about half of the videos were created by female-presenting users, around a third by male-presenting users, and the rest by creators whose gender presentation was mixed, collaborative, or not clearly identifiable. This makes sense given TikTok’s overall user base and the dominance of feminine-coded humor, lifestyle, and commentary genres that tend to drive virality on the platform.

When looking at tone, roughly one-third of the videos were serious in how they portrayed gender roles, while about 27 percent used parody or satire. A smaller portion blended humor and sincerity—often flipping between the two in the same clip. This mix of tones captures something distinct about TikTok itself: the way sincerity and irony constantly overlap. The same sound, caption, or format can mean completely different things depending on who performs it and how. That’s part of what makes these trends so powerful—they invite both imitation and reinterpretation.

In terms of valence, nearly half of the videos reinforced familiar gender stereotypes, while others either pushed back against them (around 14 percent) or combined both reinforcement and critique (about 38 percent). The overlap between these categories is important. It suggests that even when stereotypes are being “mocked,” they still circulate widely and can easily be taken at face value. Many creators seemed aware of this tension and leaned into it, using humor or exaggeration to test how far they could go without fully endorsing what they were representing.

Finally, the Notes section helped fill in what the numbers couldn’t show. Here, I recorded details about performance style, creator intent, and audience reactions—especially the comment sections, where people often made the meaning of a post explicit. Sometimes viewers laughed along and reinforced the joke; other times, they called it out or reinterpreted it. These responses often shifted how a post could be read, showing how meaning on TikTok is a shared construction between creator and audience. Together, these observations point to a platform where gender norms are not just displayed but constantly negotiated, blurred, and remixed in real time.

Results

From the 150 TikTok videos analyzed, several key patterns emerged in how gender stereotypes were performed, shared, and interpreted. Before turning to those patterns, it helps to understand what these “trends” look like in practice. On TikTok, a trend is usually a short, repeatable format — often a joke, sound, or role-play — that thousands of users adapt with their own twist. Many of the gendered trends in this study use humor and exaggeration to explore how men and women are expected to behave. For instance, videos under “She’s a 10 but…” or “The Ick” dramatize the ways people judge one another in dating contexts, while trends like “Pick-Me Girl” or “High Value Man” assign labels that turn personality types into familiar online characters. Others, such as “Female vs. Male Gaze” or “Almond Mom,” reflect how gender norms appear in everyday self-presentation, work, or family life. Across these formats, users continually remake the same cultural scripts, sometimes to mock them, sometimes to affirm them, and often doing both at once.

From this dataset, four major themes emerged: exaggerated self-awareness and performance, ironic reinforcement, gendered claims to authenticity, and the audience’s co-production of meaning. Together, these patterns show how TikTok doesn’t just repeat existing stereotypes, but constantly reworks them through humor, remixing, and audience participation.

Exaggerated Self-Awareness and Performance

Across multiple trends, creators didn’t simply show gendered behavior; they performed it to the point of caricature. In trends like “She’s a 10 but…”, “The Ick,” and “Girl Math,” humor depended on exaggeration. Creators amplified familiar traits—overthinking, dramatizing, emotional detachment—until they became absurd. For example, in “Girl Math,” women jokingly justify impulsive spending (“It was 50% off, so I basically made money”), while in “The Ick,” users overact disgust at minor habits (“He ties his shoes weird—ick”). These portrayals are not realistic; they’re intentionally over-the-top, designed to make the audience both laugh and recognize the stereotype behind the joke. 

This kind of exaggerated self-awareness often works as a form of social commentary. It lets creators acknowledge the absurdity of gender expectations while still participating in them. By performing stereotypes knowingly, users expose them whilst also keeping them alive through repetition. In the comments under these videos, audiences frequently responded with agreement rather than critique (“So real,” “That’s literally me”), showing how irony can slide back into affirmation. 

The humor here cuts both ways. It creates a shared understanding between creator and viewer—we all get the joke—but that familiarity is also what keeps these stereotypes circulating. Each reuse of the format reinforces the same gender-coded behaviors, even when the intention is to mock them.

Ironic Reinforcement

If exaggerated performance makes gender norms visible, irony makes their meaning more ambiguous. Many creators in this dataset used humor as a kind of protective layer—saying, in effect, “I’m joking, don’t take this seriously.” But that same irony often allowed stereotypes to spread unchecked. In trends like “Pick-Me Girl,” “High Value Man,” and “Looksmaxxing,” irony blurred the line between critique and endorsement. 

In “Pick-Me Girl” videos, for instance, women acted out exaggerated lines such as, “I’m not like other girls, I watch football,” using mocking tones or overdone gestures to expose how women are sometimes rewarded for rejecting femininity. Yet, in the comments, viewers often missed the irony. Many men responded earnestly (“Finally a girl who gets it”), revealing how satire can reinforce the very logic it aims to critique.

A similar pattern appeared in “High Value Man” and “Looksmaxxing” trends. Some male creators mimicked self-improvement influencers, listing ways to “raise your SMV”—social or sexual market value—as a form of parody. Others delivered nearly identical advice seriously, treating dominance, appearance, and wealth as measures of worth. Because TikTok’s format encourages repetition and remixing, both versions used the same sounds, captions, and imagery. A viewer scrolling quickly might not know which is which.

This ambiguity is central to how irony functions on TikTok. It gives creators plausible deniability—they can always claim, “It’s just a joke.” But when those jokes are repeated and liked thousands of times, they take on their own cultural weight. As researchers such as Ford and Ferguson (2004) argue,

 disparagement humor lets bias hide behind laughter, which can normalize prejudice by making it seem socially acceptable. On TikTok, that process occurs faster and has a wider reach.

Gendered Claims to Authenticity

Another major pattern that emerged was how creators performed “realness” differently across gender lines. On TikTok, authenticity functions almost like a currency — the more “real” or “relatable” someone appears, the more credible their message becomes. But what counts as authentic often depends on who’s speaking and how.

In trends such as “Almond Mom” and “Female vs. Male Gaze,” female creators often grounded their authority in emotional honesty and lived experience. In “Almond Mom,” for instance, women reenacted moments of being policed about food or body image — lines like “You really need all that?” or “I just don’t eat carbs after lunch” — to highlight how controlling, diet-obsessed parenting gets normalized as “care.” The humor was sharp but personal, inviting viewers to laugh while recognizing a familiar discomfort.

In “Female vs. Male Gaze,” creators compared what women find attractive versus what men find attractive — for example, showing a man in a cozy hoodie and messy hair (“female gaze”) next to the same man posing shirtless in a gym mirror (“male gaze”). The trend evolved into commentary on whose preferences define beauty and whose approval people are dressing or performing for. A lot of women used the trend to take back control, showing that feeling good and expressing personality can be more attractive than trying to look flawless.

Male creators, by contrast, tended to frame their authenticity through logic and control. In “Looksmaxxing” or “High Value Man” videos, they spoke in the language of optimization — “Improve your jawline with this daily routine,” “Dress in neutrals to look more put-together” — as though authenticity were something that could be engineered. This style mirrors what sociologist R.W. Connell (2005) describes hegemonic masculinity, where credibility comes from rationality and self-discipline rather than emotion.

These contrasting portrayals show how gender is performed not only through appearance but also through the emotional and social expectations tied to each gender. In “Female vs. Male Gaze,” humor exposes how beauty standards shift depending on who is doing the evaluating, and how women often must balance both sets of expectations at the same time. The joke works because viewers already understand this double bind: men are often taught to value polished or sexualized presentation, while women tend to emphasize comfort, personality, or everyday attractiveness. The humor becomes a form of critique, allowing women to exaggerate the contrast and reclaim a sense of agency by highlighting the superficiality of male standards.

Male creators, in contrast, frequently use seriousness or technical language to signal credibility. Their content rarely invites the same kind of playful self-reflection, which reinforces the idea that masculine identity is tied to control, logic, and improvement. This difference shows that what counts as “authentic” is never neutral. It is shaped by cultural expectations about how men and women are supposed to present themselves, what emotions they are allowed to express, and how they should demonstrate social value.

Audience Co-Production of Meaning

Finally, one of the most striking patterns in the data was that meaning on TikTok didn’t stop once a creator uploaded a video; it kept evolving through the comments, duets, and stitches that followed. The platform’s participatory design means that audiences aren’t just passive consumers; they’re active interpreters who shape how a post is understood. In some cases, they even flipped its meaning entirely.

For example, under videos using the “Trad Wife” hashtag, women presented domestic life through soft, vintage aesthetics like baking bread, wearing long dresses, and captioning posts with phrases like “romanticizing my life” or “making the house a home.” The comments, though, showed how differently people read the same video. Some users wrote, “This is so peaceful, I want this life,” while others fired back with, “Girl, you’d last two days without Wi-Fi.” What one viewer saw as wholesome, another saw as regressive.

A similar tension appeared under “Sigma Male” posts, where creators paired composed, slow-motion clips with motivational quotes or dark instrumentals. Some commenters mocked the tone–“bro thinks he’s in a trailer,” “POV: he ordered a black coffee once,”– while others shared the message, tagging friends and writing “real mindset.” In both cases, the humor and sincerity overlapped so tightly that it became hard to tell which was which.

Even lighter trends like “She’s a 10 but…” or “The Ick” turned gender stereotypes into an interactive game. What started as quick jokes, “He’s a 9 but claps when the plane lands,” evolved into a couple of interviews, where creators asked their partners to rate them or their exes based on trivial habits. These videos often blurred humor and discomfort: laughing through the process of being judged, while reinforcing the idea that someone’s worth can be ranked on a 1–10 scale. The comment sections amplified it further, with users chiming in to defend, mock, or one-up each example. The format made it easy for everyone to join in, but it also normalized the constant evaluation of behavior and appearance through a gendered lens.

Taken together, these patterns show that TikTok operates both as a mirror that reflects gender norms and as a generator that reshapes and intensifies those norms through viral repetition.. Its humor, speed, and remix culture allow stereotypes to mutate rather than simply repeat. Exaggeration turns expectations into shared jokes, irony disguises reinforcement as critique, authenticity becomes a gendered performance, and audiences collectively decide what each post means. The result is a feedback loop in which meaning is never fixed—gender is continuously performed, debated, and redefined in real time. This constant negotiation gives TikTok both its cultural influence and its ambivalence. The platform can challenge gender stereotypes by drawing attention to their absurdity, yet it can also reinforce them through repetition, humor, and algorithmic amplification. Gender norms on TikTok are therefore unstable. They are continually being tested, stretched, and reassembled in ways that influence how young people interpret what it means to be masculine or feminine today.

Discussion and Conclusion

Overview

This project set out to understand how gender stereotypes appear and evolve inside TikTok’s viral culture. While earlier research has shown how traditional media embed gender roles through repetition, this study shows that TikTok works differently. On this platform, gendered scripts don’t simply appear in finished form; they’re constantly being performed, joked about, and reshaped by millions of users in real time. TikTok turns stereotypes into something participatory. This participatory quality matters because it shifts who controls representation. In traditional media such as television or film, stereotypes are created by producers and writers and then delivered to audiences. On TikTok, ordinary users participate in generating, repeating, and revising those stereotypes. This makes gender norms more fluid, but also more widespread. Once a joke becomes a trend, thousands of people join in, which can turn a stereotype into shared language within days. Participation democratizes representation, but it also accelerates how quickly stereotypes spread and take root. Because viewers can immediately respond, reinterpret, or remix a creator’s video, audience participation becomes central to how stereotypes persist and evolve on TikTok.

Irony as an Unstable Form of Critique

Irony is no longer a guarantee of critique. Many of TikTok’s gendered trends rely on humor to signal self-awareness, allowing creators to distance themselves from the stereotypes they perform. But irony, in this context, is unstable. On a platform driven by repetition and speed, tone becomes more difficult to identify; satire and sincerity often look identical. When viewers encounter a video out of context, what was meant as parody can easily be read as endorsement. This suggests that irony, rather than protecting against stereotypes, can sometimes make them more durable by making repetition look like critique.

Authenticity as Gendered Performance

Authenticity is performed through gendered expectations. TikTok’s culture emphasizes “realness,” but what counts as authentic is deeply gendered. Female creators in this dataset often performed authenticity through emotional openness, confession, or vulnerability, while male creators tended to perform authority, control, or rational expertise. Both versions of “realness” might look spontaneous, but they’re still performances. What feels authentic on TikTok is often what the algorithm rewards and what audiences respond to. In that way, authenticity isn’t an escape from performance; it’s another form of it. Instead of showing who people “really are,” the platform creates a new kind of script for seeming genuine—one that is filtered through gender expectations and audience approval.

Audience Participation and the Circulation of Stereotypes

Audience participation sustains stereotypes. Meaning on TikTok doesn’t stop when a creator uploads a video; it keeps evolving through the comments, duets, and stitches that follow. Audiences, instead of just consuming gender norms, help produce them. Comment sections often turned jokes into debates or reinforced the stereotypes the creator was trying to mock. Even disagreement kept the trend in motion by boosting engagement and visibility. This shows that participation itself is what gives stereotypes their staying power. On a platform where attention equals reach, every like, repost, and argument contributes to a cycle that keeps these stereotypes circulating.

The Collapse of Tone

The collapse of tone creates ambiguity and power. In earlier forms of satire, the stance was clear—the audience could tell that the creator didn’t actually believe what they were portraying. On TikTok, that clarity often disappears. The same sound or format might be used both sincerely and ironically, and a viewer scrolling quickly might not know the difference. This tonal collapse gives the platform creative energy but also allows stereotypes to circulate without accountability. At the same time, viewers can project their own beliefs onto a trend, reading sincerity where none was intended. This collapse of tone helps explain why TikTok content spreads so fast and why stereotypes can reappear in new, more ambiguous forms.

Limitations and Future Research

This study focused on a relatively small sample of 15 viral trends and 150 TikTok posts, chosen to represent the most visible examples of gendered content. Because of that, the findings shouldn’t be taken as representative of all of TikTok or of every kind of user community. The analysis also centered on English-language videos from mainstream creator networks, which leaves out regional and subcultural spaces where gender performance might look very different.

Future research could build on this work by studying a larger or more diverse dataset, including creators from other linguistic or cultural contexts. It could also combine qualitative analysis with computational tools to track how trends spread over time, or explore how algorithmic amplification shapes which performances of gender gain visibility. Finally, interviews with creators and viewers could help explain how people understand their own participation—whether they see it as parody, sincerity, or something in between.

Overall Implications

More broadly, this study shows that gender in the age of social media is not just represented but actively produced through everyday participation. On TikTok, gender norms do not sit still; they are constantly negotiated through humor, repetition, remixing, and audience interaction. This makes stereotypes more dynamic and adaptable than in traditional media, but also more resilient. They spread faster, mutate more easily, and can be reinforced even as they are being mocked. At the same time, the platform creates space for resistance, allowing creators to expose contradictions in gender expectations or reframe them in ways that feel more authentic. The major takeaway is that participatory media like TikTok turn gender into an ongoing public performance shaped by millions of small creative acts. Understanding this process is essential for recognizing how cultural beliefs about gender are forming today, and how young people encounter, challenge, and internalize them in real time.

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