Sexualized culture on livestreaming platforms: a content analysis of Twitch.tv

This research investigates the prevalence and nature of sexualized content on Twitch.tv, a popular livestreaming platform with millions of daily viewers. The increasing concern regarding the impact of sexualized content on social media, especially on adolescents, motivates this study. Self-sexualization, where individuals portray themselves in a sexually attractive manner, is a growing trend among women on social media, often driven by social pressures to conform to beauty standards and achieve online validation. Prior research has linked exposure to sexualized content to various negative consequences, including mental health issues (anxiety, depression), body dissatisfaction, eating disorders, and the normalization of violence against women. This study focuses on Twitch.tv, examining how streamers produce and distribute content, particularly regarding gender differences in self-sexualization. The researchers aim to analyze whether women are self-sexualized more than men on Twitch.tv and if there are statistically significant differences in sexualization levels and behavior between men and women streamers.

The introduction extensively reviews existing literature on the impact of media on culture and thought, emphasizing the growing concern about sexualized content on social media and its effects on young people. It highlights studies examining self-sexualization among women and girls, the pressures to conform to beauty standards, and the resulting mental health and psychological consequences. The review also covers research on how exposure to sexualized content shapes gender attitudes, normalizes violence against women, and influences young people's understanding of sexuality. The review establishes the context for the study by highlighting the need to analyze the role of media platforms, particularly livestreaming platforms like Twitch.tv, in the dissemination of sexualized content and its impact on gender equality.

This study employed a content analysis design. The researchers developed an ad-hoc scale to measure the frequency and intensity of sexualization in Twitch.tv livestreams. The scale considered various context variables and streamer behaviors, including clothing, posture, body parts shown, image focus, mouth movements, simulation of sexual acts, and role-play. The scale allowed for classifying livestreams into three levels of intensity: non-sexualized, sexualized, and hypersexualized. The sample consisted of 1920 livestreams (960 from the “Video Games” category and 960 from the “IRL” category, which includes “Just Chatting,” “ASMR,” and “Pools, Hot Tubs & Beaches” subcategories). The top 10 videos from each subcategory were selected daily over 532 consecutive days. Videos where the streamer's image wasn't visible or used non-real images (e.g., cartoons) were excluded. The chi-square test was used to analyze statistically significant differences in sexualization levels between men and women and across categories. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were performed to assess the scale's validity and reliability. Cronbach’s alpha was calculated to assess internal consistency.

The exploratory factor analysis revealed two factors: “Context” (clothing, posture, image focus, exposure of body parts) and “Behavior” (mouth movements, simulated sexual acts, role-play). The scale demonstrated good reliability (Cronbach’s alpha > 0.7). Descriptive analysis revealed that while a higher percentage of men streamed overall (61.2% vs. 38.8% for women), the distribution varied significantly by category. Male streamers dominated in “Games” and “Just Chatting,” while female streamers predominated in “ASMR” and “Pools, Hot Tubs & Beaches.” Critically, the study found significantly higher levels of sexualization among female streamers compared to male streamers across all levels of intensity (non-sexualized, sexualized, and hypersexualized). Chi-square tests showed significant differences in sexualization levels between men and women (p < 0.001). In categories like ASMR and Pools, Hot Tubs & Beaches, a substantial proportion of female streamers were categorized as sexualized or hypersexualized, whereas male streamers were predominantly in the non-sexualized category. The results consistently indicated that women, particularly in specific categories, self-sexualized more frequently and intensely than men.

The findings strongly support the hypothesis that women are more frequently and intensely self-sexualized on Twitch.tv than men. The significant differences across categories suggest that platform features and audience expectations may contribute to these disparities. The study highlights the complex interplay between self-sexualization, audience engagement, and economic incentives on livestreaming platforms. While some might argue that self-sexualization empowers women economically, the study underscores the potential negative consequences, including the perpetuation of harmful gender stereotypes and the normalization of sexual objectification, especially for young viewers. The findings contribute to the understanding of online gender dynamics and call for further research into the long-term impact of self-sexualization on women's mental health and well-being.

This study provides valuable insights into the sexualization of content on Twitch.tv, revealing significant gender disparities. Women are more frequently and intensely self-sexualized than men, particularly within specific categories. The findings underscore the need for critical awareness of the platform's role in perpetuating harmful gender norms and the potential negative impact on young users. Future research could explore the motivations behind self-sexualization among female streamers, the long-term consequences of exposure to sexualized content on viewers, and the effectiveness of platform interventions to mitigate these issues.

The study's sample, while large, may not be fully representative of the entire Twitch.tv user base. The reliance on observable behaviors and visual cues for assessing sexualization might overlook other factors that influence sexualization. The study focused on two broad categories and might not capture the diversity of content across all Twitch.tv channels. The cross-sectional nature of the study limits inferences about causal relationships.