GangTok: Street gang content,culture,and roleplay on TikTok

Abstract

Research on street gangs’ digital presence has focused on networked platforms like Facebook where visibility reflects interpersonal ties. Newer, short-form, algorithmically curated environments such as TikTok reorder these dynamics by privileging performance, spectacle, and trend alignment. This mixed-methods study analyzes 397 publicly available TikTok videos associated with Latino gangs in Chicago to address four key questions: the genres of gang-related content present, the extent to which these genres circulate, how creators perform and negotiate authenticity, and how platform-specific performances complicate interpretations of offline identity. We identify three genres: (1) place-based memorials that document gang geography; (2) traditional gangbanging performances that assert identity and provoke rivals; and (3) role-playing simulations of gang life in Grand Theft Auto V. These genres circulate unevenly: users tend to post within a single niche, and place-based and traditional gangbanging content receive disproportionately higher engagement than role-playing videos. Across genres, credibility is both central and contested, as symbolic fluency can substitute for verifiable street ties. We use “GangTok” as a descriptive shorthand for this ecology, where authentic, adjacent, and imitative performances coexist. Findings reveal how TikTok amplifies familiar gang repertoires while blurring insider–outsider boundaries, underscoring the limitations of content-level inference in algorithmically mediated publics.

Keywords

gangs performative identity digital gang culture roleplay gangs and social media

Introduction

Since the first iPhone came out in 2007, the study of gangs in digital spaces has shifted from foundational concerns about access and connectivity to more complex questions about how gang identity, conflict, and affiliation are performed and sustained online. Early scholarship asked whether gang-involved individuals even used the internet, highlighting the digital divide and infrastructural barriers (Moule et al., 2013; Papachristos, 2005; Pyrooz et al., 2015). As smartphone adoption and platform use expanded—particularly among youth—scholars turned their attention to how social media functioned as an extension of street life (for reviews see Fernández-Planells et al., 2021; Moore and Stuart, 2022; Pyrooz and Moule, 2019). Research has shown that gang-affiliated individuals use digital spaces to perform violent identities (Lauger and Densley, 2018; Leverso and Hsiao, 2021; Storrod and Densley, 2017; Stuart, 2020; Van Hellemont, 2012; Worthen et al., 2025), signal affiliation (Leverso et al., 2025a), memorialize peers (Patton et al., 2018), and engage in online conflicts that often mirror or correlate with offline tensions (Hsiao et al., 2023; Leverso et al., 2024; Moule et al., 2017).

Earlier work framed the digital street as an extension of the physical one (Lane, 2016) largely because networked platforms like Facebook, Twitter (X), and YouTube were organized around pre-existing social ties and personal followings. TikTok, a short-form video-sharing platform characterized by “interest-driven, algorithmic publics” (Bhandari, 2024), reconfigures this logic, shifting visibility from network ties to performance. On TikTok, authenticity remains tied to offline connections but is often judged through curated cues—gang signs, drill rap soundtracks, filters, and location tags—that suggest identity without confirming membership. The platform’s recommendation engine amplifies the most eye-catching performances, creating a feedback loop where performativity is rewarded with visibility (Hund, 2023; Serazio, 2023).

This dynamic does not mean street reputation is irrelevant. Rather, it shows how algorithmic arenas create space where digital fluency and symbolic repertoires of gang culture can temporarily substitute for traditional status. We use “gang culture” in a performance-oriented sense, following Moore and Stuart’s (2024) call for clarity: not as fixed oppositional values, but as repertoires and products enacted, recognized, and circulated through performance. On TikTok, identity is shaped as much by visible cues and algorithmic amplification as by street-level ties.

TikTok invites us to examine how gang identities circulate in algorithmic publics. Drawing on a purposive sample of public TikTok videos documenting Latino gangs in Chicago, this study examines the forms of gang-related content that emerge on the platform, how widely those forms circulate in terms of visibility and engagement, and how creators perform and negotiate authenticity under conditions of algorithmic amplification. We also consider the challenges these platform-specific performances pose for interpreting gang identity and affiliation offline.

We analyzed 397 TikTok videos linked to Chicago’s Latino gang landscape, using keyword sampling informed by domain expertise. Through qualitative content analysis, we identified an emergent digital subculture we call GangTok—gang-related content shaped by TikTok’s algorithmic logics of visibility. In this study, we use “genre” to refer to recurrent, recognizable forms of content production that combine shared visual conventions, narrative logics, and interactional purposes. Using this approach, we identify three dominant genres within GangTok: (1) Place-Based Gang Content, mapping geography and collective memory of gang-affiliated neighborhoods through graffiti-tagged intersections; (2) Traditional Gangbanging videos, asserting identity and provoking rivals through territorial claims and performances of threat; and (3) Role-Playing Video Gangs, a novel genre in which users simulate gang life in modded versions of Grand Theft Auto, blending gaming culture with established gang repertoires. We supplement this typology with descriptive statistics on visibility, engagement, and algorithmic reach.

Together, these findings update digital gang research by showing how TikTok’s affordances reshape identity and circulate symbolic violence within a media ecology governed as much by esthetics as by street reputation. In an era when how and when one posts can matter more than who one is, GangTok highlights the need to re-examine gang culture, social media, and the digital performance of identity.

Literature review

Gangs and the digital street

Early research on gangs in online spaces raised foundational questions about access, technological literacy, and the digital divide (Décary-Hétu and Morselli, 2011; Morselli and Décary-Hétu, 2013; Moule et al., 2013; Whittaker et al., 2020; Womer and Bunker, 2010). In 2005, Papachristos observed that “few gang members ever discuss or mention the Internet,” noting that many lacked the hardware or skills to participate (p. 53). With smartphones now in the hands of over 95% of U.S. teens (Anderson and Jiang, 2018), such barriers have largely disappeared. Today, youth across racial and socioeconomic lines routinely engage with social media, and for gang-involved individuals, the internet is not separate from the street but an extension of it (Pyrooz et al., 2024).

This convergence is captured in Lane’s (2016) concept of the digital street: a space where offline codes of gang life—status, identity, and territoriality—are enacted, negotiated, and contested through digital media. Rather than assuming a universal script, research shows that gang signaling and online practices are “glocalized”—rooted in local histories, languages, and gendered street worlds, yet reshaped by the affordances and audiences of global platforms (see Van Hellemont and Densley, 2019). In highly media-saturated contexts such as Chicago, rituals once confined to specific corners or alleyways are translated online through threats, call-outs, and visual markers such as weapons, graffiti, or hand signs, often layered with slang, hashtags, or coded language that signal affiliation or disrespect (Patton et al., 2013; Pyrooz et al., 2015). At the same time, these digital repertoires can look quite different in other cultural settings, even as social media similarly becomes a stage for grief and loyalty, with memorials to deceased members, drill-rap tributes, and anniversary posts reaffirming bonds (Lauger and Densley, 2018; Patton et al., 2018; Stuart, 2020).

These performances do not merely reflect identity; they help constitute it. Digital bravado and disrespect can escalate tensions, with studies in North America and Europe documenting links between online expression and offline violence (Densley, 2020; Hyatt et al., 2021; Lane, 2018; Moule et al., 2017; Storrod and Densley, 2017; Stuart, 2020; Urbanik and Haggerty, 2018). Lauger et al. (2019) argue that online strain can spill offline, while Patton et al. (2019) identify direct threats, call-outs, and public humiliation as especially potent triggers for retaliation, particularly when personalized. Consistent with broader gang scholarship, these digital spaces are also heavily gendered, with participation and visibility shaped by the fact that most gang-related online activity—like gangs themselves—remains predominantly male (Leverso et al., 2025b).

Recent studies formalize these insights using digital trace data. Hsiao et al. (2023) suggest platforms now form a third pillar of gang dynamics, alongside the “corner” and the “crew.” Leverso et al. (2025b) empirically test the online–offline link, finding that while many disputes remain virtual, street violence often drives online posts rather than the reverse. These findings complicate narratives that blame social media for rising violence, suggesting instead a feedback loop in which digital and geographic conflicts mirror and intensify one another.

From networked to algorithmic platforms

Most prior work has focused on networked platforms such as Facebook, Twitter (X), and YouTube, where visibility flows through established social ties. On these sites, conflict and credibility are typically localized within networks, allowing researchers to trace digital interactions back to offline relationships and rivalries. As summarized in Figure 1, TikTok differs fundamentally in how it produces visibility and credibility. While legacy platforms and TikTok share core features (e.g. networking capabilities, content sharing, ad-based revenue), their distribution logics diverge. Facebook and X primarily amplify content within established networks, with selective algorithmic boosts. TikTok’s algorithm-driven For You Page instead surfaces content from unknown creators based on engagement rather than social ties, allowing disputes to scale well beyond local networks. Its younger user base and emphasis on creative video further foster distinct norms around authenticity and credibility, quite different from the text-centric, news-oriented discourse of older platforms (Abidin, 2020).

Figure 1.

Platform comparison.

To situate these shifts, we turn to longstanding debates about gang culture. Scholars have framed it variously as values, repertoires, or products (Moore and Stuart, 2024). Early criminology emphasized oppositional values guiding behavior (e.g. Anderson, 2000), but this “culture-as-values” perspective has been criticized for pathologizing gangs and overlooking heterogeneity. A second view sees culture as repertoires or toolkits—resources youth draw on strategically across contexts (Rios, 2011; Swidler, 1986). Garot (2010) extends this argument, showing that gang identity is contingent and audience-dependent, with authenticity always negotiated. A third approach foregrounds culture as products—music, images, slang that circulate for recognition or gain (Conquergood, 1993; Stuart, 2020). Lauger (2024) illustrates this in the context of gang-affiliated rap, where exaggeration, performance, and claims to authenticity intersect. Just as rap verses codify scripts even when partially detached from lived experience, TikTok skits reproduce, stylize, and reshape gang culture.

Grouping these perspectives into values, repertoires, and products is a useful shorthand, but the differences matter for understanding digital gang culture. Values-based accounts treat culture as a moral and prescriptive order that orients behavior and binds members to shared expectations about loyalty, retaliation, and respect. Performance-oriented work, by contrast, emphasizes that culture is enacted in situ, emerging through audience-dependent displays, face-work, and the negotiation of credibility in specific encounters (Goffman, 1959). The cultural-product perspective highlights how images, sounds, and symbols detach from their original contexts and circulate as transferable artifacts, accruing meaning through repetition rather than through embodied participation. These are not minor variations on a theme but distinct ways of conceptualizing what culture is: a moral code, an interactional accomplishment, or a circulating commodity.

TikTok complicates and connects these strands by transforming situated performances into widely circulating products, making it increasingly difficult to discern where embodied interaction ends and cultural artifact begins. In Castells (1996) terms, identity work on TikTok takes place within real virtuality, where digital representations feed back into, and structure, lived experience. At the same time, many clips operate as Baudrillardian simulacra—signs detached from their referents—producing a hyperreality in which curated cues can substitute for embodied affiliation (Baudrillard, 1994). From this perspective, gang culture online is not only a set of values, repertoires, or products, but also a field of simulations staged, circulated, and adjudicated within algorithmically organized publics.

Play, participation, and the attention economy

These dynamics suggest that gang culture online cannot be reduced to reflections of street life. It is also shaped by broader digital repertoires of play and participation. Scholars of digital play and participatory culture emphasize how avatars, simulations, and online publics provide arenas for experimenting with identity through performance (Jenkins, 2006; Taylor, 2006). On TikTok, these dynamics are intensified through features such as duets, stitches, and reaction videos, which generate what Zulli and Zulli (2022) call imitation publics—communities cohering not through dialog but through replication of recognizable formats and trends. Memes and insider references, from sound clips to coded gestures and hashtags, further structure participation by offering shared templates that users can remix to signal belonging. In this environment, visibility depends less on street credibility than on performative fluency: knowing how to “do,” “speak,” and meme TikTok in ways that align with platform logics and audience expectations.

These dynamics reflect TikTok’s position within the broader attention economy, where human attention is a scarce and valuable resource (Davenport and Beck, 2002; Hund, 2023). Platform algorithms tend to elevate content that is emotionally engaging, provocative, or easily shareable, producing feedback loops in which visibility can function as a marker of influence and legitimacy (Fisher, 2021; Hari, 2022). For gang-involved creators, this reward structure may encourage the stylization of familiar street codes into more visually salient or algorithm-friendly forms. Colors, hand signs, or drill-rap snippets can circulate widely and sometimes detach from their original contexts, enabling both insiders and outsiders to remix them in the pursuit of attention. TikTok’s editing tools, including voiceovers, audio reuse, and asynchronous reactions, further complicate the task of distinguishing genuine affiliation from mimicry or play (Leverso et al., 2025a).

These shifts raise several questions: How is gang identity rendered legible in a trend-driven feed? What happens when symbols migrate out of context or are reproduced by users with varying proximity to street life? How do gang-involved youth recognize themselves in a representational environment shaped by remix, repetition, and algorithmic sorting? These issues matter because TikTok gang content spans explicit displays of identity as well as choreographed skits, trend-driven clips, and remixed archival footage that blur the lines between parody, homage, and self-representation. Such practices unsettle the boundary between performing a gang persona and participating in gang culture, making authenticity an unstable accomplishment rather than a fixed attribute (Van Hellemont, 2012; Van Hellemont and Densley, 2019).

Building on performative traditions in gang research (Conquergood, 1993; Garot, 2010), we suggest that these representations are reconfigured within algorithmic publics, where visibility itself can operate as symbolic capital. The circulation of Grand Theft Auto-based roleplay, for example, illustrates how gang tropes migrate into digital arenas shaped simultaneously by gaming logics and by street codes (Jenkins, 2006; Taylor, 2006). The shift from networked to algorithmic environments thus presents a growing area of inquiry in digital gang studies—one that requires updated conceptual tools, attention to platform design, and responsive methods. We use GangTok as a descriptive shorthand for this emerging arena, where authenticity, simulation, and algorithmic amplification intersect, and where visibility interacts with, and sometimes obscures, traditional markers of street-level identity.

Method

Research team and context

This study draws on original data collected from TikTok, focusing on content associated with Latino street gangs in Chicago. We selected this focus because it aligns with the research team’s expertise and long-standing engagement with Chicago’s Latino gang landscape. Given the complexity of gang culture outlined above (particularly how identity, symbolism, and communication vary across neighborhoods and platforms), we prioritized contextual depth over generalizability.

To support interpretation, the research team incorporated multiple forms of embedded expertise. Two domain experts—one a former gang leader and the other a long-time South Side member—served not merely as reviewers but as cultural interpreters whose knowledge derives from sustained involvement in Chicago’s Latino gang landscape. Their familiarity with territorial boundaries, historic rivalries, and symbolic repertoires enabled the identification of spatial, esthetic, and linguistic cues that fall outside conventional analytic coding. They recognized specific blocks, alleys, murals, corner stores, and color combinations; decoded slang, insults, and references to deceased individuals; and interpreted gestures, clothing choices, and sound selections that carry meaning only within Chicago’s gang ecosystem.

The dataset itself reflected insider knowledge. Many clips re-enact distinctly local practices and scripts, including rammer car culture, freestyle and drill performances, drive-bys, ambushes orchestrated through gendered deception, “caught lacking” incidents, gas station altercations, and everyday rituals like selling loose cigarettes (“squares”) or cruising on New Year’s Eve. These were not generic tropes but highly localized depictions that require familiarity with Chicago’s gang landscape to interpret appropriately.

The lead researcher also contributed experiential insight, having spent over a decade gang-involved in Chicago before pursuing an academic career. Combined with domain-expert consultation and systematic coding procedures, this layered expertise helped reduce the risk of misclassification. While affiliations cannot always be verified, these multiple vantage points suggest that much of the content reflects insiders’ or adjacent participants’ knowledge of gang life.

Sampling and data collection

To identify relevant TikTok content, the lead researcher consulted the domain experts to compile current gang names, slang, hashtags, and digital practices. This iterative process combined exploratory searches with expert refinement; the experts also sought feedback from individuals currently or recently gang-involved. Their role was not to verify individual gang involvement, but rather the final keyword list of gang names, acronyms, neighborhood references, symbolic language, and common suffixes or prefixes signaling allegiance (e.g. “king love,” “two-six nation”) or opposition (e.g. “king killer,” “KK”).

Two trained undergraduate research assistants—selected for their experience and expertise with social media—used the keyword list to conduct systematic searches. After training in identifying gang-related visual and linguistic markers, they flagged public-facing TikTok accounts, videos, and hashtags. For example, the hashtag #AlmightySaints returned 28 posts, but only 15 were retained after excluding unrelated references to Christian saints. The lead researcher then reviewed each flagged post to confirm relevance.

Of the 10 accounts identified, two were excluded because their content was unrelated to Chicago-based Latino gangs. This issue was most common for nationally affiliated gangs, such as the Latin Kings, where content often originated outside Chicago. The final dataset included 397 video posts from eight TikTok accounts.

All videos and associated metadata were collected using web-scraping tools in February 2025. For each post, we archived the video and metadata for hashtags and engagement metrics (views, likes, comments, shares). The dataset spans 1 year: March 1, 2024, to February 28, 2025. Figure 2 provides user-level summary statistics on video volume and average engagement.

Figure 2.

Summary statistics by GangTok user. (a) Number of videos. (b) Views per video. (c) Likes per video. (d) Shares per video.

Content analysis and coding

Following data collection, the lead researcher conducted an open-ended review to identify recurring themes, visual elements, and representational patterns. This grounded analysis produced an inductive content typology, which informed the structured coding scheme. The final typology included three categories defined and analyzed in the Results section: Place-Based Content, Traditional Gangbanging, and Role-Playing Video Gangs.

Each video was then coded for qualitative features commonly associated with gang-related media, including firearms, graffiti, gang colors, depictions of violence, hand signs, identifiable street signs or locations, drugs, alcohol, references to deceased individuals, depictions of law enforcement, and comments supportive or antagonistic toward the featured gang. Each feature was coded dichotomously (1 = present, 0 = absent). To ensure consistency, all four authors independently coded a random subset of 50 videos. After resolving discrepancies and refining the schema, the lead author applied the finalized codes to the full dataset (N = 397).

Ethical considerations

All data were publicly available on TikTok at the time of collection. Given the sensitivity of the material—including potential youth involvement, depictions of real-world conflict, or graphic violence—we do not name individual accounts or users. While some content appears fictionalized or gamified (e.g. video game roleplays), other videos may involve real persons or incidents. To minimize risks of harm, identification, or stigmatization, we anonymize all data and present findings only in aggregate. This approach follows best practices for ethical digital research involving vulnerable or criminalized populations (Urbanik et al., 2020; Urbanik and Roks, 2020).

Analytical strategy

This study employs a mixed-methods approach to examine both the structure and meaning of gang-related content on TikTok. The core analysis is qualitative, using thick description and an inductively developed typology of three genres: (1) Place-Based Content, (2) Traditional Gangbanging, and (3) Role-Playing Video Gangs. Each video was coded for symbolic features—such as hand signs, graffiti, territorial markers, violence, or memorials to deceased individuals—as well as narrative and performative elements. Drawing on visual, textual, and audio cues, we interpret how users construct identity, signal affiliation, and navigate gang culture within a platform shaped by algorithmic logics.

To complement this qualitative analysis, we present descriptive statistics on engagement and content features. Metrics such as views, likes, comments, and hashtag frequency highlight which genres attract the most attention and situate different forms of gang expression within TikTok’s “attention economy” (Davenport and Beck, 2002). This pairing of close interpretation with broader contextualization offers a layered understanding of digital gang performance.

We treat the dataset as a time-bounded “snapshot” of gang-related TikTok, rather than an exhaustive archive. Collecting a year of content provides a robust basis for analysis while approximating the experience of a user scrolling the For You Page. Methodologically, this is analogous to snowball sampling: it does not capture every possible pathway of exposure but reflects the repertoires and symbolic practices circulating most visibly. Inductive thematic analysis is well-suited to this terrain, as TikTok’s affordances—short-form video, remix tools, and trend-driven circulation—require grounded, flexible coding. This approach follows best practices in exploratory digital research (Urbanik et al., 2020) and enables us to identify recurring cultural logics of representation without presuming how the algorithm operates.

Findings

Our analysis identified three dominant modes of gang performance on TikTok: documenting history, performing street status and threat, and simulating gang life through video game roleplay. Each reflects a distinct way that identity, conflict, and memory are negotiated in the platform’s algorithmic environment. The sections that follow examine these three genres of GangTok in detail, followed by quantitative patterns of visibility and engagement.

Qualitative findings: The three components of GangTok

Place-based

These videos often appear as slow driving tours or walk-throughs, with the videographer narrating the significance of specific locations. Graffiti tags, murals, and neighborhood boundaries serve as visual cues, while captions or voiceovers identify which sets once dominated—or still dominate—particular blocks. Hashtags such as #oldblock and #gangterritory reinforce the spatial framing, while background music often adds a reflective or nostalgic tone.

Creators display detailed knowledge of gang geography, though their current affiliations are not always clear. One prominent page, for example, describes its mission as documenting “the art and history of our streets,” adding, “I do not promote violence.” Captions frequently name gangs directly—for example, “Welcome to the Darkside” (Figure 3, column 1, row 1)—signaling territorial specificity and highlighting culturally significant sites such as a gang’s “motherland.”

Figure 3.

Visual display of gang-related content on TikTok.

The comment sections are particularly dynamic. Some users express solidarity (“King Love, ”), while others taunt rivals (“King Killer”) or question a group’s legitimacy (“they never outside”). Still others share personal memories—“they used to be deep”—or ask clarifying questions if unfamiliar with Chicago’s landscape. The result is an eclectic thread where memory, reputation, and hyperlocal knowledge are collectively negotiated.

Unlike more confrontational genres, this content emphasizes spatial remembrance over direct threat. Yet it engages core dimensions of gang culture—territoriality, symbolic ownership, and collective memory (see Decker et al., 2022)—serving as a digital archive of gang-affiliated space, part map, part oral history.

Traditional gangbanging

The second genre most directly extends past practices of “internet banging” (Patton et al., 2013), adapted to TikTok’s mobile-first, visually driven format. Here, users assert gang identity through symbolic or literal acts of dominance, often staged in rival territory. Common elements include flashing gang signs, displaying firearms, urinating on enemy turf, tagging over graffiti, and bending or destroying street signs.

One video, for example, shows a deceased rival’s name written upside-down (a traditional insult), paired with a sarcastic Easter reference (mocking the rival’s bunny symbol), and ending with a custom license plate reading “Two XIS”—a coded inversion of “Six.” Hashtags such as #twosix, #sdz, #chiraq, or #kingkiller extend reach while signaling affiliation. In another clip, a rival is filmed urinating on a street sign labeled “Stone 59k,” (Figure 3, column 2, row 2).

As with place-based content, the comments act as secondary arenas for contestation. Supporters use cues like “King Love” or emojis, while rivals post “King Killer” or challenge authenticity. Commenters sometimes invoke street lore, referencing notorious figures (e.g. a gang member tied to the shooting of a DEA agent), or debate whether individuals are “really outside” or simply posturing for views. The familiar suffixes “love” and “killer” illustrate how older vernacular continues in digital form.

Yet these videos also show meaningful shifts. Content is often more stylized and symbolic than incendiary, likely reflecting TikTok’s stricter moderation compared to Facebook or X. Several posts disappeared soon after upload, suggesting platform enforcement shapes user behavior. Performances also increasingly occur in enemy spaces rather than home turf—claiming rival territory as spectacle—reflecting both the risks and rewards of TikTok’s attention economy. A notable innovation is the ritual of metal street sign bending, a repeated act of visible disrespect well-suited to short-form video but rarely documented by earlier studies of online gang media.

These shifts suggest continuity in symbolic logic—asserting status, bravery, and disrespect—alongside reconfiguration by TikTok’s affordances. In the GangTok era, performances are directed not only to known peers or rivals but to algorithmically expanded audiences. The boundary between real and performative violence, private threat and public display, grows increasingly blurred.

Role-playing video gangs

The third genre represents a novel digital phenomenon: gang roleplay through video games, most notably the FiveM modification for Grand Theft Auto V (GTA V). On custom multiplayer servers, players recreate virtual Chicago landscapes with factional territories, scripted rivalries, and coded interactions that mirror real-world street culture. Edited into TikTok-friendly highlight reels, these clips depict simulated drive-bys, tagging turf, evading police, orchestrating ambushes, or performing freestyles. Users dramatize not only spectacular events such as shootings but also mundane rituals—cruising blocks, pumping gas, or selling “loose squares.” In several cases, players reenacted high-profile Chicago incidents, such as the viral “caught lacking in the gangway” video, overlaying gameplay with audio from YouTube or drill tracks to transform tragedy into digital folklore. For instance, one clip shows a rival gang’s modified truck struck by a trailer in enemy territory, while another depicts a Latin King avatar “sliding” into Manic Latin Disciple space to commit a homicide in broad daylight (see Figure 3). Together, these reenactments highlight how offline events migrate into gamified simulations.

What distinguishes this genre is its interactive, collaborative structure. Users craft avatars, coordinate events through Discord (an instant messaging and Voice over Internet Protocol social platform), and improvise plots in real time, blurring the line between player and persona. The digital arena functions as both cultural simulation and collective storytelling, where street codes are reproduced, reframed, and reimagined in a sandbox world. Here, gang identity becomes modular: avatars can be tailored, conflicts replayed, and performances remixed, intertwining play, commentary, and performance.

Unlike traditional gangbanging videos—often produced by individuals with confirmed affiliations—roleplay content is usually created by users whose real-world ties are uncertain. Yet the symbolic language adheres closely to Chicago street codes. Avatars reference specific gangs, reenact notorious shootings, and layer drill music, slang, and viral sounds to reinforce authenticity. One popular clip shows four avatars piling into a sedan while drill music blares and gunfire takes down rivals on a street corner; another depicts players loitering and rapping at a gas station, mimicking the everyday rhythms of gang life. Commenters often remarked that the thickly rendered scenes felt “too real to be just a game.” Although less common overall, these videos sometimes drew thousands of views, suggesting that novelty and entertainment value were especially rewarded by TikTok’s algorithm.

Comment sections add another layer of engagement. Some viewers praised the realism (“Bro made it look just like the South Side”), others critiqued inaccuracies (“That’s not even how the real LKz roll”), while many asked how to join the servers—indicating that the pages functioned as gateways into a participatory subculture. Familiar cues such as “King Love ” or “SD4L” further blurred the line between fan, observer, and participant.

Taken together, these roleplay videos illustrate how TikTok amplifies simulations that merge gaming logics with gang repertoires. In this space, visibility accrues not from embodied risk but from digital fluency, as authenticity is projected through stylized performance. GangTok here is not simply a continuation of online signaling but a transformation of it, producing a digital archive shaped as much by platform design as by the street codes it emulates.

Quantitative findings: Descriptive statistics and interpretation

While the three genres reveal distinct cultural and symbolic dimensions of GangTok, they also differ in how they circulate and gain traction. To examine how these content types function within TikTok’s algorithmic environment, we present descriptive statistics on video frequency, engagement metrics, content features, hashtag use, and comment sentiment. These patterns show how each genre performs on the platform and which forms of gang-related content are most amplified.

Video frequency and engagement

Figure 4 is a series of bar charts presenting the number of videos, three metrics of engagement (views per video, likes per video, and shares per video), and overall composition of the eight users’ posts across the three categories of GangTok content.

Figure 4.

Summary statistics by GangTok category. (a) Number of videos. (b) Views per video. (c) Likes per video. (d) Shares per video. (e) Category composition by user.

Starting with panel A, there is a clear difference in the volume of content being produced across the three categories, with our dataset including over 300 videos in the Role-Playing category, compared to just over 40 each for Place-Based and Traditional Gangbanging. Despite large differences in the amount of content between online role-playing and the other two categories, we nonetheless find that the typical amount of engagement for a video is substantially higher for posts in the Place-Based and Traditional Gangbanging categories. These two categories average three to five times the number of views as Role-Playing Video Gang posts (Panel B), in addition to three to six times as many likes (Panel C) and more than twice as many shares (Panel D). Finally, when looking at who posts different content categories, we observe a general tendency for users to only post within a single category, with all accounts but User 7 posting most or all content to just one category (Panel E).

Content prevalence

Figure 5 is a heatmap showing the prevalence of specific content types within posts of a particular category. Each category is represented as a row of cells, with each cell colored according to the prevalence of the content. Brighter colors indicate greater presence of some form of content (e.g. street signs and locations), with the numbers within each cell indicating the prevalence percentage. The forms of content used in this analysis are based on gang subculture, both historical and contemporary, and are informed by the literature (Conquergood, 1993; Decker and Van Winkle, 1996; Hagedorn and Macon, 1988; Lauger, 2012; Stuart, 2020).

Figure 5.

Content prevalence by GangTok category.

Each category has a relatively distinct pattern of content found within its posts. Place-Based videos always focus on street signs and locations within Chicago and the vast majority include graffiti in some form (86%). However, these are the only two clear markers related to gang culture present. Hand signs, colors, and all other forms of content considered in this analysis were not found in any of these videos. Traditional Gangbanging videos had more variety in their content. While hand signs were the most common element of gang subculture present (41%), there was otherwise at least some prevalence for all but one category (Drugs, Alcohol, & Smoking). In contrast to the other two categories, Role-Playing Video Gangs content focused on violence and guns, with most videos including these elements (59% and 61%, respectively). Violence and guns were relatively rare among Traditional Gangbanging posts, though they were occasionally observed (7% and 12%, respectively).

Hashtag use

Among the 397 videos in our dataset, all but one feature hashtags as the only text caption accompanying the post. Hashtags are keywords or phrases preceded by the # symbol to categorize and track content on social media; they are essential for understanding how TikTok content creators attempt to connect their posts with other users. Figure 6 is a heatmap focused on assessing which hashtags were used across the different categories, using the 15 most frequently observed hashtags in our sample. Like the prior figure, cells are colored according to prevalence, with the specific statistic noted in the middle.

Figure 6.

Hashtag prevalence by GangTok category.

Starting with Place-Based videos, the most used hashtags were “art” (84%), “chicago” (77%), and “peace” (77%), since the videos in this category focused on documenting and showcasing Chicago gang neighborhoods, especially their graffiti, rather than directly capturing gangs in these contexts. Reflecting the fact that these accounts also tended to focus on historically Latino neighborhoods, the next most common hashtags were “folks” (51%), “littlevillage” (26%), and “latinkings” (23%). Outside these hashtags, Place-Based content tended not to overlap with the other frequently used hashtags observed.

Among Traditional Gangbanging videos, there was some overlap in the most used hashtags (“chicago” at 54%, “littlevillage” at 51%), but otherwise we observed a distinct set that were predominantly observed among this category. Specifically, the most used hashtag was “fyp” (73%), an effort to broadly promote content to other users’ algorithm-driven For You Page. Other top hashtags among this category included “chitown” (44%), “latinking” (44%), “rammer” (39%), and “fypシ” (27%).

Finally, among Role-Playing Video Gangs posts, we again see only minor overlap with the other categories. “Chicago” was the most used hashtag, but otherwise, we observe four hashtags that were essentially only used in this category. Here, “fivem” (75%), “server” (54%), “gta” (47%), and “rp” (13%) were the unique hashtags used to promote this content and identify other users with this interest across the platform.

Reply comment sentiment

Our final quantitative analysis focuses on reactions to the video posts by other users, investigating whether gangs were mentioned in reply comments, and if so, what sentiment was present in these reactions (Figure 7).

Figure 7.

Reply sentiment by GangTok category.

Like with the prior analyses, we tend to see the greatest difference between Role-Playing Video Gangs posts and the other two categories. For Place-Based and Traditional Gangbanging, we observe that most posts have some gang-related response, with most having a mix of both positive and negative sentiments toward individual gangs in these replies (53% and 54%, respectively). In contrast, most Role-Playing Video Gangs posts received little gang-related response in their comments. Otherwise, another observation is that Place-Based posts were more likely to have strictly positive comments in response compared to the other categories, and only about a quarter of these videos did not have any gang-related responses altogether.

Taken together, these quantitative patterns illuminate how GangTok’s different genres not only reflect varied expressive practices, but also experience divergent levels of visibility and reception within TikTok’s algorithmic ecosystem. Despite being less frequent, Place-Based and Traditional Gangbanging videos received disproportionately high engagement, suggesting that authenticity cues and symbolic proximity to street life continue to attract attention. Role-Playing Video Gangs, though dominant in volume, often lack such cues, resulting in lower engagement and less gang-related interaction in comment threads. Hashtag use further distinguishes the genres, with each leveraging a unique set of tags to connect with specific publics—whether those rooted in neighborhood identity, gang clout, or gaming subcultures. Finally, sentiment analysis of comments reveals that while some audiences respond positively to memorialization and performance, others introduce antagonism or disengage entirely. These patterns highlight the importance of platform logic in shaping which representations of gang life are seen, shared, and interpreted, setting the stage for the discussion that follows.

Discussion

Our findings on short-form, interest-driven platforms such as TikTok invite scholars to revisit assumptions drawn from research on networked sites like Facebook and Twitter (Leverso and Hsiao, 2021). We use GangTok as a descriptive shorthand for a cluster of gang-related content in our dataset: place-based memorials, traditional gangbanging performances, and role-playing videos. The term is not advanced as a new analytical framework but as a heuristic to foreground how visibility and performance are reconfigured within algorithmic publics, where credibility can rest on esthetic fluency as much as on verifiable street ties. In this environment, TikTok content does not simply mirror gang dynamics offline; rather, it participates in how those dynamics are interpreted, circulated, and sometimes reworked.

With respect to our first research question, we identified three recurring genres of gang-related TikTok content: (1) Place-Based videos that memorialize and map gang-affiliated neighborhoods; (2) Traditional Gangbanging clips that assert identity through symbolic threat and territorial performance; and (3) Role-Playing Video Gangs, in which users simulate gang life through modded Grand Theft Auto V roleplay servers. These categories align with earlier work documenting online repertoires of grief, bravado, territoriality, and threat on social media (Patton et al., 2013; Pyrooz et al., 2015; Storrod and Densley, 2017). What distinguishes TikTok is not the presence of new scripts but the curatorial and memetic environment through which familiar ones are amplified. Features such as trending sounds, recommended hashtags, and low-friction remixing reward content that is visually striking or emotionally charged, regardless of the poster’s network connections or offline status.

TikTok’s affordances also help explain the distinctiveness of the role-playing genre. Gamification—understood as the use of game design elements such as points, levels, and competitive scripts in non-game contexts (Chou, 2015; Fisher, 2021)—offers a useful lens for interpreting this ecology. Street gangs have long incorporated game-like dynamics, from initiation rituals and territorial contests to status hierarchies (Densley, 2012; Felson, 2006; Harding, 2014). Yet on TikTok and GTA V role-play servers, these dynamics are transformed into stylized, low-risk performances where users can simulate conflict, status claims, or group belonging for entertainment. These simulations constitute a form of virtual status work, a symbolic economy where recognition accrues through spectacle and memetic alignment rather than through embodied participation.

Our second research question asked how platform design shapes the circulation of these genres. Nearly all creators posted exclusively within one genre, suggesting that the recommendation system may amplify homophily and reinforce representational silos (Zhou, 2024). While we cannot observe exposure patterns directly, the structure of the dataset indicates that audiences likely encounter distinct, genre-specific portrayals of gang culture. Engagement patterns further underscore TikTok’s selective visibility: place-based and traditional gangbanging content—though less common—elicited higher interaction than role-playing videos, aligning with broader evidence that youth-oriented algorithms elevate emotionally intense or sensationalized content (Spring, 2024). These patterns suggest that GangTok is stratified rather than uniform, shaped by the interplay of user practices, memetic formats, and algorithmic amplification.

Turning to our third question, we know that offline, “keeping it real” entails aligning behavior with group norms, demonstrating commitment and risk exposure, and achieving recognition within relevant networks (Densley, 2013; Leverso et al., 2025a). On TikTok, however, authenticity is mediated by an attention economy structured around trends, sound snippets, editing styles, and platform-native memes (Hund, 2023). Symbolic fluency (i.e. knowing how to “do” TikTok) can function as a proxy for insider status. Hand signs, color schemes, captions, fashion, and meme templates can all be deployed by creators with varying degrees of proximity to actual gangs.

This environment produces what Lauger (2024) identifies in the context of gang rap: simulations and exaggerations that do not deviate from cultural practice but are woven into it. TikTok videos similarly encode scripts linking disrespect to retaliation or bravado to reputation, yet the cues for evaluating authenticity shift from embodied presence to metrics of reaction—views, likes, shares—and to iterative audience feedback.

To answer our fourth research question, we find that audience adjudication plays a crucial role in this process. Whereas the preceding discussion centers on how creators signal authenticity, this question highlights how audiences evaluate and contest those claims. Comment sections, duets, and stitches frequently debate who is “real” and who is “clout chasing.” These interactions make authenticity a collectively negotiated performance rather than a stable attribute. Some users demand demonstration of local knowledge or street ties; others treat gang esthetics as freely available symbolic resources for humor, irony, or self-promotion. The result is not simply ambiguity, but an ongoing tension between signaling offline affiliation and signaling platform fluency.

A central implication of this environment is the increasing difficulty of distinguishing insiders from outsiders on TikTok. Content circulating under gang-associated hashtags included confirmed gang members, youth from gang-affected neighborhoods who are not affiliated, and non-local creators adopting gang esthetics for entertainment or experimentation. Because TikTok rewards repetition, recognizable symbols, and emotional intensity, simulations, parodies, reenactments, and authentic depictions are presented in a shared visual vernacular (Sujon and Ntalla, 2025). For viewers lacking local or cultural context, affiliation, adjacency, and imitation can become visually indistinguishable.

These interpretive challenges mirror concerns raised in related research on the criminalization and misreading of digital street culture (Kubrin and Nielson, 2014; Lane et al., 2018; Stuart, 2020). Ilan (2020) demonstrates how “street-illiterate” interpretations of drill music treat stylized performance as a literal threat, producing counterproductive and stigmatizing interventions. Fraser and Atkinson (2014) similarly show how intelligence-led policing can “make up” gangs through looping processes of categorization and surveillance that rely on ambiguous cultural signals rather than grounded local knowledge. Our findings extend this literature to TikTok, where algorithmic amplification further complicates efforts to infer threat, intent, or affiliation from visibility alone.

Methodologically and ethically, these dynamics underscore the limits of interpreting short-form video content in isolation. Qualitative coding informed by domain expertise can help differentiate among insiders, adjacent youth, and outsiders, but it cannot fully resolve ambiguities generated by stylized mimicry and memetic circulation. Integrating digital trace data, interviews, and ethnographic insight will be essential for unpacking how platform features shape the perceived legitimacy of gang-related content.

These findings also connect to longstanding debates about gang culture as values (Anderson, 2000), repertoires (Rios, 2011; Swidler, 1986), or products circulated for recognition (Conquergood, 1993; Stuart, 2020). The TikTok environment invites an extension of this literature: in algorithmic publics, gang culture also functions as a mediated performance, continually reshaped through imitation, remix, simulation, and amplification. The real/performance dichotomy presented by Garot (2010) and others does not disappear but becomes layered and unevenly legible. For gang-outsiders, platform fluency may matter more than physical proximity. For gang-insiders, offline status still matters, but its representation is filtered through the same memetic and algorithmic logics as outsider content.

This study focuses on publicly available TikTok videos associated with Chicago’s Latino gang landscape. While this approach allows for culturally grounded interpretation, it limits generalizability to other communities, gang structures, and regional ecologies. TikTok’s recommendation algorithm is also opaque; we observe engagement patterns and genre clustering but we cannot determine precisely why specific videos are elevated. Further, our dataset captures a single moment within a rapidly evolving platform that may shift as affordances, moderation practices, and user norms change. Future research should examine GangTok across cities, incorporate longitudinal data, and integrate interviews or ethnographic work to understand how youth interpret and navigate these digital arenas.

Conclusion

This study advances scholarship on gangs and digital media by showing how TikTok’s interest-driven design reconfigures the production and circulation of gang-related content. Drawing on a uniquely detailed dataset grounded in Chicago’s Latino gang landscape, we identify three distinct genres—traditional gangbanging performances, place-based memorial and mapping content, and role-playing simulations—that together reveal how gang identities are curated, stylized, and gamified within short-form algorithmic publics. The central contribution is not the cataloging of these genres but the demonstration that TikTok’s affordances and memetic logics condition how familiar gang scripts circulate, blur, and acquire meaning.

By advancing GangTok as a heuristic rather than a typology, we show how credibility in this environment is negotiated at the intersection of symbolic fluency, audience adjudication, and algorithmic visibility. This perspective extends longstanding debates about gang culture as values, repertoires, or cultural products by highlighting a fourth dimension: culture as mediated performance, continually reshaped through imitation, remix, and amplification. These insights help explain why insiders, adjacent youth, and outsiders can occupy the same representational space and why authenticity becomes a contested accomplishment rather than a fixed attribute.

Methodologically, the study illustrates the value of combining insider expertise with systematic qualitative coding to distinguish between lived affiliation, adjacency, and simulation. This approach highlights both the possibilities and limits of content-level analysis in contexts where authenticity is contested and where platform logics blur boundaries between representation and reenactment.

These findings also carry practical implications. Practitioners and policymakers increasingly encounter gang-related content online, but often lack the contextual knowledge needed to distinguish credible signals from stylized mimicry. Recognizing how platform dynamics shape representation is essential for avoiding misclassification and designing responses that neither over- nor under-react to what young people post and consume.

More broadly, this study suggests that digital environments do not merely reflect gang culture; they participate in its ongoing production. As participatory publics and role-playing genres evolve, criminology will need frameworks that connect insights from gang research with media studies, game studies, and cultural sociology. Understanding how gang tropes migrate, transform, and gain traction across platforms is not only a theoretical task but a practical one, with implications for youth engagement, public perception, and the institutional responses that follow.

Footnotes

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Partial support for this research came from a Eunice Kennedy Shriver National Institute of Child Health and Human Development research infrastructure grant to the Center for Studies in Demography and Ecology at the University of Washington (R24 HD042828).

ORCID iDs

John Leverso

James A. Densley

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Author biographies

John Leverso is an Assistant Professor at the University of Cincinnati’s School of Criminal Justice. He is a sociological criminologist whose research focuses on urban street gangs and health criminology.

Chris Hess is an Assistant Professor of Sociology at Kennesaw State University whose research focuses on neighborhood stratification, housing inequalities and computational approaches to social science.

Dr. James A. Densley is Professor and Department Chair of Criminology and Criminal Justice at Metro State University and Co-Founder of The Violence Prevention Project Research Center ("The Violence Project") at Hamline University. He has authored nine books and edited two others, including The Oxford Handbook of Gangs and Society. His research has been featured by global media and published in 70+ scientific journals and 100+ popular outlets, including The New York Times, TIME, The Wall Street Journal, and The Washington Post.

Kristonn A. A. Stubbs is a Doctoral Student in Criminal Justice at the University of Cincinnati. His research interest includes gangs, justice-involved youth, and health criminology.

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