A Critical Discourse Analysis of Online Misogynistic Trolling in the Gaming Community: A Mixed Methods Study

محورهای موضوعی : تحلیل گفتمان

Haider Saad Yahya Jubran ¹ , Fatemeh Karimi ² , Basim Jubair Kadhim Al-Jameel ³ , Ehsan Rezvani ⁴

1 - Department of English Language, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
2 - Department of English, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
3 - Open Educational College, Najaf Center, Ministry of Education, Iraq, Najaf.
4 - Department of English Language, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

تاریخ دریافت : 1403/12/21 تاریخ پذیرش : 1404/01/24 تاریخ انتشار : 1403/12/26

کلید واژه: cognitive processes, critical discourse analysis, gaming community, online misogynistic trolling, power dynamics,

چکیده مقاله :

Online gaming platforms foster vibrant communities but are increasingly recognized as environments where harmful interactions, including misogynistic trolling, proliferate. This study examined the linguistic strategies and discursive devices utilized in online misogynistic trolling within specific online gaming communities. The objectives included exploring how power dynamics and gender ideologies are represented in this discourse and analyzing the cognitive processes and mental representations that influence the production and reception of such communications. For the qualitative analysis, critical discourse analysis methods were employed, including Fairclough’s three-dimensional model, van Dijk’s socio-cognitive approach, and the ideological square. The quantitative analysis entailed frequency counts and inferential statistics (chi-square tests) to uncover relationships between variables identified in the qualitative phase, specifically, linguistic features, cognitive processes, and platform type. The dataset for analysis comprised 200 online texts (forum posts, comments, messages) and related data sources (gaming streams, videos, podcasts, social media interactions), primarily sourced from platforms like Reddit, 4chan, and Twitch, alongside interviews and focus groups with affected gamers. The analysis indicated a significant prevalence of misogynistic language, including sexual objectification, insults, and threats, along with notable instances of racist, religious, homophobic, and ableist hate speech. Cognitive processes like stereotyping, prejudice, and emotional reactions drive the creation and reception of hateful messages. Understanding the mechanisms of such harmful discourse is crucial for developing strategies to mitigate its impact, which holds broader relevance for creating respectful interactions in various online settings, including educational ones.

چکیده انگلیسی:

Online gaming platforms foster vibrant communities but are increasingly recognized as environments where harmful interactions, including misogynistic trolling, proliferate. This study examined the linguistic strategies and discursive devices utilized in online misogynistic trolling within specific online gaming communities. The objectives included exploring how power dynamics and gender ideologies are represented in this discourse and analyzing the cognitive processes and mental representations that influence the production and reception of such communications. For the qualitative analysis, critical discourse analysis methods were employed, including Fairclough’s three-dimensional model, van Dijk’s socio-cognitive approach, and the ideological square. The quantitative analysis entailed frequency counts and inferential statistics (chi-square tests) to uncover relationships between variables identified in the qualitative phase, specifically, linguistic features, cognitive processes, and platform type. The dataset for analysis comprised 200 online texts (forum posts, comments, messages) and related data sources (gaming streams, videos, podcasts, social media interactions), primarily sourced from platforms like Reddit, 4chan, and Twitch, alongside interviews and focus groups with affected gamers. The analysis indicated a significant prevalence of misogynistic language, including sexual objectification, insults, and threats, along with notable instances of racist, religious, homophobic, and ableist hate speech. Cognitive processes like stereotyping, prejudice, and emotional reactions drive the creation and reception of hateful messages. Understanding the mechanisms of such harmful discourse is crucial for developing strategies to mitigate its impact, which holds broader relevance for creating respectful interactions in various online settings, including educational ones.

منابع و مأخذ:

Burgess, M. C. R., Stermer, S. P., & Burgess, S. R. (2007). Sex, lies, and video games: The portrayal of male and female characters on video game covers. Sex Roles, 57(5–6), 419–433. https://doi.org/10.1007/s11199-007-9250-0
Cao, R., & Lee, R. (2020). HateGAN: Adversarial generative-based data augmentation for hate speech detection. Proceedings of the 28th International Conference on Computational Linguistics, 6327–6338. https://doi.org/10.18653/v1/2020.coling-main.557
Colder Carras, M., van Rooij, A. J., van de Mheen, D., Musci, R., Xue, Q. L., & Mendelson, T. (2017). Video gaming in a hyperconnected world: A cross-sectional study of heavy gaming, problematic gaming symptoms, and online socializing in adolescents. Computers in Human Behavior, 68, 472–479. https://doi.org/10.1016/j.chb.2016.11.060
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). Sage publications.
De la Torre Sierra, A., & Guichot-Reina, V. (2024). Women in video games: An analysis of the biased representation of female characters in current video games. Sexuality & Culture, 28, 1–29. https://doi.org/10.1007/s12119-024-10286-0
De Palma, P. (2001). Viewpoint: Why women avoid computer science. Communications of the ACM, 44(6), 27–30. https://doi.org/10.1145/376134.376145
Deligianni, A., & Horne, Z. D. (2023). Analysing hate speech towards women on Reddit. PsyArXiv. https://doi.org/10.31234/osf.io/fsrq7
Deng, Z. (2024). “They don’t mean to hurt”: Female gamers’ reluctance in recognizing and confronting sexism in gaming as an online-offline juxtaposition. New Media & Society. Advance online publication. https://doi.org/10.1177/14614448241287831
Dill, K. E., Gentile, D. A., Richter, W. A., & Dill, J. C. (2005). Violence, Sex, Race, and Age in Popular Video Games: A Content Analysis. In E. Cole & J. H. Daniel (Eds.), Featuring females: Feminist analyses of media (pp. 115–130). American Psychological Association. https://doi.org/10.1037/11213-008
Dill, K. E., & Thill, K. P. (2007). Video game characters and the socialization of gender roles: Young people’s perceptions mirror sexist media depictions. Sex Roles, 57(11–12), 851–864. https://doi.org/10.1007/s11199-007-9278-1
Downs, E., & Smith, S. L. (2010). Keeping abreast of hypersexuality: A video game character content analysis. Sex Roles, 62(11–12), 721–733. https://doi.org/10.1007/s11199-009-9637-1
ElSherief, M., Nilizadeh, S., Nguyen, D., Vigna, G., & Belding, E. (2018). Peer to peer hate: Hate speech instigators and their targets. Proceedings of the International AAAI Conference on Web and Social Media, 12(1). https://ojs.aaai.org/index.php/ICWSM/article/view/15038
Fairclough, N. (1995). Critical discourse analysis: The critical study of language. Longman.
Fairclough, N. (2010). Critical discourse analysis: The critical study of language (2nd ed.). Routledge.
Falsetti, S. A., & Resnick, H. S. (1995). Helping the victims of violent crime. In J. R. Freedy & S. E. Hobfoll (Eds.), Traumatic stress: From theory to practice (pp. 263–285). Plenum Press.
Fortuna, P., & Nunes, S. (2018). A survey on automatic detection of hate speech in text. ACM Computing Surveys, 51(4), 1-30. https://doi.org/10.1145/3232676
Fox, J., & Bailenson, J. N. (2009). Virtual virgins and vamps: The effects of exposure to female characters’ sexualized appearance and gaze in an immersive virtual environment. Sex Roles, 61(3–4), 147–157. https://doi.org/10.1007/s11199-009-9599-3
Ghozali, I., Sungkono, K. R., Sarno, R., & Abdullah, R. (2023). Synonym based feature expansion for Indonesian hate speech detection. International Journal of Electrical and Computer Engineering, 13(1), 1105–1112. https://doi.org/10.11591/ijece.v13i1.pp1105-1112
Ging, D., Lynn, T., & Rosati, P. (2020). Neologising misogyny: Urban Dictionary’s folksonomies of sexual abuse. New Media & Society, 22(5), 838–856. https://doi.org/10.1177/1461444819870306
Heng, S., Zhao, H., & Wang, M. (2021). In-game social interaction and gaming disorder: A perspective from online social capital. Frontiers in Psychiatry, 11, Article 468115. https://doi.org/10.3389/fpsyt.2020.468115
Jakubowska, H. (2024). Who counts as a woman? A critical discourse analysis of petitions against the participation of transgender athletes in women’s sport. International Review for the Sociology of Sport, 59(2), 203–221. https://doi.org/10.1177/10126902231194570
Jagayat, A., & Choma, B. L. (2021). Cyber-aggression towards women: Measurement and psychological predictors in gaming communities. Computers in Human Behavior, 120, Article 106753. https://doi.org/10.1016/j.chb.2021.106753
Kay, A. C., Laurin, K., Fitzsimons, G. M., & Landau, M. J. (2014). A functional basis for structure-seeking: Exposure to structure promotes willingness to engage in motivated action. Journal of Experimental Psychology: General, 143(2), 486–491. https://doi.org/10.1037/a0034462
Keya, A. J., Kabir, M. M., Shammey, N. J., Mridha, M. F., Islam, M. R., & Watanabe, Y. (2023). G-BERT: An efficient method for identifying hate speech in Bengali texts on social media. IEEE Access, 11, 75873–75887. https://doi.org/10.1109/ACCESS.2023.3299021
Kennedy, H. W. (2002). Lara Croft: Feminist icon or cyberbimbo? On the limits of textual analysis. Game Studies: The International Journal of Computer Game Research, 2(2). http://www.gamestudies.org/0202/kennedy/
Koenig, A. M., & Eagly, A. H. (2014). Evidence for the social role theory of stereotype content: Observations of groups’ roles shape stereotypes. Journal of Personality and Social Psychology, 107(3), 371–392. https://doi.org/10.1037/a0037215
Kowert, R., Breuer, J., & Quandt, T. (2017). Women are from FarmVille, men are from ViceCity: The cycle of exclusion and sexism in video game content and culture. In R. Kowert & T. Quandt (Eds.), New perspectives on the social aspects of digital gaming: Multiplayer 2 (pp. 104–120). Routledge. https://doi.org/10.4324/9781315629308-9
Lupu, Y., Sear, R., Velásquez, N., Leahy, R., Restrepo, N. J., Goldberg, B., & Johnson, N. F. (2023). Offline events and online hate. PLoS ONE, 18(1), Article e0278511. https://doi.org/10.1371/journal.pone.0278511
Marwick, A. E., & Lewis, R. (2017). Media manipulation and disinformation online. Data & Society Research Institute. https://datasociety.net/pubs/oh/DataAndSociety_MediaManipulationAndDisinformationOnline.pdf
McKinney, V., Wilson, D., Brooks, N., O’Leary-Kelly, A., & Hardgrave, B. (2008). Women and men in the IT profession. Communications of the ACM, 51(2), 81–84. https://doi.org/10.1145/1314215.1314229
Mulvey, L. (1999). Visual pleasure and narrative cinema. In L. Braudy & M. Cohen (Eds.), Film theory and criticism: Introductory readings (5th ed., pp. 833–844). Oxford University Press.
Obermaier, M., Schmid, U. K., & Rieger, D. (2023). Too civil to care? How online hate speech against different social groups affects bystander intervention. European Journal of Criminology, 20(3), 817–833. https://doi.org/10.1177/14773708231156328
Phillips, W. (2015). This is why we can’t have nice things: Mapping the relationship between online trolling and mainstream culture. MIT Press.
Pira, A. (2015). Misogyny in the world of online gaming? A critical discourse analysis about how female gamers are portrayed in the Swedish Media [Unpublished master’s thesis]. Lund University.
Ponterotto, D. (2014). Trivializing the female body: A cross-cultural analysis of the representation of women in sports journalism. Journal of International Women’s Studies, 15(2), 94–111. https://vc.bridgew.edu/jiws/vol15/iss2/7
Potter, W. J. (2022). Analysis of definitions of media literacy. Journal of Media Literacy Education, 14(2), 27–43. https://doi.org/10.23860/JMLE-2022-14-2-3
Rollè, L., Ramon, S., & Brustia, P. (2019). Editorial: New perspectives on domestic violence: From research to intervention. Frontiers in Psychology, 10, Article 641. https://doi.org/10.3389/fpsyg.2019.00641
Salminen, J., Luotolahti, J., Almerekhi, H., Jansen, B. J., & Jung, S.-G. (2018). Neural network hate deletion: Developing a machine learning model to eliminate hate from online comments. In A. Voiskounsky, O. Smirnova, & A. Ershov (Eds.), Digital Transformation and Global Society. DTGS 2018. Communications in Computer and Information Science (Vol. 859, pp. 24–36). Springer. https://doi.org/10.1007/978-3-030-01437-7_3
Santoniccolo, F., Trombetta, T., Paradiso, M. N., & Rollè, L. (2023). Gender and media representations: A review of the literature on gender stereotypes, objectification and sexualization. International Journal of Environmental Research and Public Health, 20(10), Article 5770. https://doi.org/10.3390/ijerph20105770
Sarkeesian, A. (2013, March 7). Damsel in distress: Part 1 — Tropes vs women in video games [Video]. YouTube. https://www.youtube.com/watch?v=X6p5AZp7r_Q
Sękowska-Kozłowska, K., Baranowska, G., & Gliszczyńska-Grabias, A. (2022). Sexist hate speech and the international human rights law: Towards legal recognition of the phenomenon by the United Nations and the Council of Europe. International Journal for the Semiotics of Law - Revue internationale de Sémiotique juridique, 35(3), 1017–1039. https://doi.org/10.1007/s11196-022-09884-8
Shaw, A. (2015). Gaming at the edge: Sexuality and gender at the margins of gamer culture. University of Minnesota Press. https://doi.org/10.5749/minnesota/9780816693153.001.0001
Shruthi, P., & Kumar, A. K. M. (2020). Novel approach for generating hybrid features set to effectively identify hate speech. Inteligencia Artificial, 23(66), 97–111. https://doi.org/10.4114/intartif.vol23iss66pp97-111
Ștefăniță, O., & Buf, D.-M. (2021). Hate speech in social media and its effects on the LGBT community: A review of the current research. Romanian Journal of Communication and Public Relations, 23(1), 47–55. https://doi.org/10.21018/rjcpr.2021.1.322
Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In W. G. Austin & S. Worchel (Eds.), The social psychology of intergroup relations (pp. 33–47). Brooks/Cole.
Vallerga, M., & Zurbriggen, E. L. (2022). Hegemonic masculinities in the ‘Manosphere’: A thematic analysis of beliefs about men and women on The Red Pill and Incel. Analyses of Social Issues and Public Policy, 22(2), 602–625. https://doi.org/10.1111/asap.12308
Van Dijk, T. A. (1988). News analysis: Case studies of international and national news in the press. Lawrence Erlbaum Associates.
Van Dijk, T. A. (2008). Discourse and context: A sociocognitive approach. Cambridge University Press.
Wachs, S., & Wright, M. F. (2018). Associations between bystanders and perpetrators of online hate: The moderating role of toxic online disinhibition. International Journal of Environmental Research and Public Health, 15(9), Article 2030. https://doi.org/10.3390/ijerph15092030
Walsh, A., & Leaper, C. (2020). A content analysis of gender representations in preschool children’s television. Mass Communication and Society, 23(3), 331–355. https://doi.org/10.1080/15205436.2019.1664593
Williams, G. (2014). Are you sure your software is gender-neutral? Interactions, 21(2), 36–39. https://doi.org/10.1145/2524808
Williams, M. L., Burnap, P., Javed, A., Liu, H., & Ozalp, S. (2020). Hate in the machine: Anti-Black and anti-Muslim social media posts as predictors of offline racially and religiously aggravated crime. The British Journal of Criminology, 60(1), 93–117. https://doi.org/10.1093/bjc/azz049
Wood, W., & Eagly, A. H. (2002). A cross-cultural analysis of the behavior of women and men: Implications for the origins of sex differences. Psychological Bulletin, 128(5), 699–727. https://doi.org/10.1037/0033-2909.128.5.699
Zakaria, M., Ali, A., & Abdul Aziz, A. (2022). Online gaming: Exploratory of the communication process and current scenario of virtual community development. International Journal of Academic Research in Business and Social Sciences, 12(11), 827–842. https://doi.org/10.6007/IJARBSS/v12-i11/14739

متن کامل:



Mixed Methods Studies in English Language Teaching (MMSELT) 

1(3), 76-103. https:/doi.org/10.71873/mslt.2024.1201765

 

Research Article

A Critical Discourse Analysis of Online Misogynistic Trolling in the Gaming Community: A Mixed Methods Study 

Haider SaadYahya Jubran1, Fatemeh Karimi2, Basim Jubair Kadhim AlJameel3, Ehsan Rezvani4

1 Department of English, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

2 Department of English, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran (Corresponding author) 

3 Open Educational College, Najaf Center, Ministry of Education, Iraq, Najaf 

4 Department of English, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

 

Abstract Online gaming platforms foster vibrant communities but are increasingly recognized as environments where harmful interactions, including misogynistic trolling, proliferate. This study examined the linguistic strategies and discursive devices utilized in online misogynistic trolling within specific online gaming communities. The objectives included exploring how power dynamics and gender ideologies are represented in this discourse and analyzing the cognitive processes and mental representations that influence the production and reception of such communications. For the qualitative analysis, critical discourse analysis methods were employed, including Fairclough’s three-dimensional model, van Dijk’s socio-cognitive approach, and the ideological square. The quantitative analysis entailed frequency counts and inferential statistics (chi-square tests) to uncover relationships between variables identified in the qualitative phase, specifically, linguistic features, cognitive processes, and platform type. The dataset for analysis comprised 200 online texts (forum posts, comments, messages) and related data sources (gaming streams, videos, podcasts, social media interactions), primarily sourced from platforms like Reddit, 4chan, and Twitch, alongside interviews and focus groups with affected gamers. The analysis indicated a significant prevalence of misogynistic language, including sexual objectification, insults, and threats, along with notable instances of racist, religious, homophobic, and ableist hate speech. Cognitive processes like stereotyping, prejudice, and emotional reactions drive the creation and reception of hateful messages. Understanding the mechanisms of such harmful discourse is crucial for developing strategies to mitigate its impact, which holds broader relevance for creating respectful interactions in various online settings, including educational ones. Keywords: cognitive processes, critical discourse analysis, gaming community, online misogynistic trolling, power dynamics

Cite as: Saad Yahya Jubran, H., Karimi, F., Jubair Kadhim AlJameel, B., & Rezvani, E. (2024).  A critical discourse analysis of online misogynistic trolling in the gaming community: A mixed methods study. Mixed Methods Studies in English Language Teaching, 1(3), 76-103.  https://doi.org/10.71873/mslt.2024.1201765

1. Introduction

Contemporary video games function as complex virtual social environments fostering distinct norms and communities, often enhanced by features promoting social connection which studies link to friendship development and enjoyment (Colder Carras et al., 2017; Heng et al., 2021). However, inherent game mechanics like ranking systems introduce power dynamics that can negatively influence behavior. Higher ranks may correlate with increased influence and aggression, potentially aligning with social dominance theories where high status relates to negative actions influenced by societal norms of gender and power (Zakaria et al., 2022). Consequently, online gaming spaces can foster both positive interactions and significant cruelty and hate speech, amplified by technology and anonymity (Fortuna & Nunes, 2018).

The rapid expansion of the internet has intensified online misogynistic rhetoric, creating an emotionally charged atmosphere distinct from traditional media, largely fueled by the anonymity that empowers aggression without consequence (Fortuna & Nunes, 2018; Keya et al., 2023). This situation presents societal challenges, sparking debates on regulation, governmental responsibility, and balancing free speech with protection from harm, ultimately impacting democratic ideals and political discourse online (Ghozali et al., 2023; Lupu et al., 2023). Confronting online hate speech, especially its disproportionate impact on marginalized groups facing gender-based hate, is crucial (Cao & Lee, 2020).

Online misogynistic discourse threatens social cohesion and rights, thriving in participatory online cultures where anonymity and lack of accountability normalize incivility and hate speech (Phillips, 2015). The gaming community, predominantly young, is susceptible to peer pressure and adopting harmful attitudes, potentially exacerbated by underdeveloped critical thinking skills, misinformation, and echo chambers facilitated by anonymity (Marwick & Lewis, 2017; Sękowska-Kozłowska et al., 2022). Negative media portrayals and attention-seeking can also fuel hate speech (Salminen et al., 2018). Recognizing gender-based bias as hate speech is vital, as research suggests links between online harassment and real-world harm, an issue potentially worsened by right-wing populism, though studies specifically on online misogyny and violence against women remain limited, particularly post-pandemic (Lupu et al., 2023; Obermaier et al., 2023; Ștefăniță & Buf, 2021; Ghozali et al., 2023). Notably, the critical examination of negative discursive practices like misogyny within these engaging online environments represents a significant research gap (Deligianni & Horne, 2023).

Understanding the cognitive mechanisms behind producing and receiving online misogyny, its effect on public discourse, and victim coping strategies is essential but significantly under-researched (ElSherief et al., 2018; Keya et al., 2023). There is an urgent need for holistic interventions to address misogynistic discourse (Deligianni & Horne, 2023; Shruthi & Kumar, 2020; Wachs & Wright, 2018) to foster more inclusive and equitable digital environments. Therefore, grounded in Critical Discourse Studies (CDS), this research aimed to identify linguistic strategies in online misogynistic discourse within gaming, explore the reflected power dynamics and gender ideologies, investigate the enabling cognitive processes, and understand its impact, guided by the following research questions:

RQ1. What linguistic strategies and discursive devices are employed in online misogynistic discourse within the gaming community?

RQ2. What are the cognitive processes and mental representations that facilitate the production and reception of online misogynistic discourse in the gaming community, and is there a statistically significant association between these cognitive processes and the specific online platforms on which this discourse occurs?

RQ3. How does online misogynistic discourse in the gaming community shape public discourse, attitudes, and potential normalization, as perceived by those targeted? 

2. Literature Review

Misogyny, broadly understood as the dislike, contempt, or hatred directed toward women, manifests in diverse ways, encompassing stereotypes, objectification, discrimination, and even violence (Falsetti & Jackson, 1995). Within the complex web of influences shaping gender perceptions, media holds a particularly significant position (Rollè et al., 2019). The pervasive nature of media, constant exposure to its messages, and its demonstrable role in molding beliefs, attitudes, and societal expectations have made it a focal point for scholarly inquiry. Various theoretical frameworks attempt to elucidate the mechanisms through which media exerts its influence, including its impact on identity formation (Kay et al., 2014), the establishment of behavioral scripts and cognitive schemas (Rollè et al., 2019), long-term cultivation processes affecting worldviews (Potter, 2022), and broader socialization processes (Koenig & Eagly, 2014).

The gaming industry’s development is closely tied to the Information Technology (IT) sector, and both fields exhibit a persistent gender imbalance, with significant underrepresentation of women (Pira, 2015). Women reportedly show less interest in IT careers compared to men and often have shorter tenures if they enter the field (McKinney et al., 2008), sometimes prioritizing job security over a passion for technology, unlike many male counterparts (McKinney et al., 2008). Lower female enrollment in computer science programs further indicates this trend (De Palma, 2001). Williams (2014) argues this imbalance stems from a culture that impedes women’s progress, advocating for active intervention beyond mere research. He proposes acknowledging bias, setting measurable goals, and implementing adaptable strategies to foster change.

Furthermore, media representations frequently contribute to the problem by stereotyping female gamers as incompetent or inadequate (Ponterotto, 2014), reinforcing the idea of gaming as a male domain where women are marginalized or reduced to tropes like the damsel in distress (Jakubowska, 2024). Research on the harassment and marginalization experienced by female gamers often highlights toxic geek masculinity and problematic gender representations in-game content as key factors (Walsh & Leaper, 2020; Wood & Eagly, 2002; Vallerga, & Zurbriggen, 2022; Pira, 2015; Santoniccolo et al., 2023). Some online platforms, lacking effective content moderation, can become breeding grounds for ‘networked misogyny,’ systematically reinforcing negative attitudes (Ging et al., 2020). Kowert et al. (2017) modeled this exclusion progressively: starting with a gendered gaming culture deterring women, leading to their underrepresentation in the industry, which in turn fosters the creation of gendered game content (stage two), ultimately contributing to abusive language and behaviors among male gamers (final stage).

A consistent finding across decades of gaming research concerns the problematic representation of female characters, who are typically: 1) numerically fewer than male characters; 2) less likely to have significant narrative roles; and 3) more frequently hypersexualized (Shaw, 2015; Downs & Smith, 2010; Williams et al., 2020; Burgess et al., 2007; Dill & Thill, 2007; Dill et al., 2005; De la Torre Sierra & Guichot-Reina, 2024). Hypersexualization involves not only revealing attire but also often features unrealistic body proportions unattainable for average women (Downs & Smith, 2010). Beyond physicality, female characters are frequently confined to limiting personality archetypes, such as the binary of the innocent ‘virgin’ versus the seductive ‘vamp’ (Fox & Bailenson, 2009). Sarkeesian (2013) argues that regardless of these superficial differences, female characters often function primarily as decoration or rewards for male protagonists, with their sexuality prioritized over agency, even when depicted as strong figures like Lara Croft (Kennedy, 2002). This objectification aligns with Mulvey’s (1999) concept of the “male gaze,” where visual media constructs female characters primarily for the voyeuristic pleasure of a presumed heterosexual male audience.

This extensive body of literature concerning gender disparities and negative portrayals in gaming and IT provides the essential context for this study’s CDA of online misogynistic trolling. The study’s significance lies in its potential to illuminate the specific linguistic strategies and discursive practices employed in such trolling, reveal the power dynamics and gender ideologies at play, and investigate the underlying cognitive processes facilitating this harmful discourse. By examining the real-world impact of this hate speech on targeted individuals and public attitudes, the research aimed to contribute knowledge that can inform efforts to combat online hate and promote gender equality in digital spaces. 

3. Method

3.1. Design

This study utilized an explanatory sequential mixed-methods design (Creswell & Plano Clark, 2018), beginning with a qualitative phase followed by a quantitative phase. The initial qualitative stage employed CDA to explore and identify key linguistic strategies, power dynamics, gender ideologies, and underlying cognitive processes within online misogynistic discourse in the gaming community (qualitative variables included these elements plus participant experiences). Subsequently, the quantitative phase measured the frequency of the identified linguistic features and cognitive processes and statistically examined the association between these cognitive processes and the specific online platforms (Reddit, 4chan, Twitch) where the discourse originated (quantitative variables included frequency counts and platform type). The purpose of this quantitative stage was to help explain and generalize patterns observed qualitatively. By integrating both approaches, the study aimed to achieve a nuanced contextual understanding from the CDA and interview data, complemented by statistically informed conclusions about the prevalence and distribution of misogynistic content and associated cognitive patterns.

3.2. The Corpus of the Study

The data set for the present study was composed of a collection of 200 online texts (forum posts, comments, and messages) and related data sources (excerpts from gaming streams, videos, podcasts, and social media posts) that were relevant to the research question of online misogynistic discourse and hate speech in the gaming community. The corpus included data publicly available from popular gaming websites and platforms frequented by gamers, such as Reddit, 4chan, and Twitch. Additionally, the corpus included data from interviews and focus group discussions with 30 volunteer participants identifying as victimized gamers (primarily women or non-binary individuals) aged 18-35 from the United States and Europe, who actively participate in online multiplayer games hosted on or discussed via platforms like Reddit, 4chan, and Twitch. The selected data spanned a specific period, starting from early 2024, to capture relatively recent discourse and dynamics surrounding online hate speech within the gaming community. This period reflected the constantly evolving nature of the gaming industry and online gaming communities, and it included contemporary examples related to the research topic. Sampling for the online texts aimed for diversity across platforms and types of interaction, while participants for interviews/focus groups were recruited via online forums and snowball sampling, focusing on individuals who had experienced misogynistic behavior. Theoretical Framework

3.3. Theoretical Framework

This study used CDA (CDA) to examine online hate speech and misogynistic trolling within the gaming community. It primarily employed Fairclough’s three-dimensional framework to analyze the discourse as text (linguistic features), discursive practice (production/consumption in online contexts), and social practice (relation to power structures and ideologies). This was complemented by van Dijk’s socio-cognitive approach, which focused on the underlying mental representations (like stereotypes and prejudice) and involved analyzing discourse structures at macro (themes), super (organization), and micro (detailed linguistic/rhetorical choices) levels. Together, these frameworks enabled a comprehensive analysis of the language used, its production context, cognitive underpinnings, and socio-political implications within online gaming communities.

3.4. Instruments

The primary analytical instruments employed in this study were the CDA frameworks themselves, specifically Fairclough’s (2010) three-dimensional model and Van Dijk’s (1988, 2008) socio-cognitive model. These models provided the core theoretical lens for interpreting the qualitative data derived from the online texts. Based on key concepts drawn from these frameworks, such as specific linguistic strategies, types of cognitive processes, and indicators of power dynamics, a detailed coding scheme was developed and iteratively refined throughout the analysis process.

The raw material subjected to analysis, constituting the data corpus, comprised the collected set of 200 online texts and related contextual data, supplemented by the verbatim transcripts generated from the interviews and focus groups. To guide the collection of this supplementary qualitative data, semi-structured interviews and focus group guides were carefully developed. These guides contained open-ended questions specifically designed to facilitate in-depth discussions with victimized gamers, encouraging them to share detailed accounts of their experiences with online misogyny, its perceived impacts on them, and the coping strategies they employed.

For managing and analyzing the substantial volume of qualitative data gathered from both the online texts and the interview/focus group transcripts, NVivo software was utilized. This tool facilitated the systematic organization, coding (including thematic and content analysis), and identification of recurring patterns, themes, and discursive strategies within the dataset. Finally, for the quantitative analysis phase involving frequency counts and the chi-square test of independence, appropriate statistical software, such as SPSS or R, was employed to perform the necessary calculations.

3.5. Procedure

Data collection involved gathering publicly available online texts from Reddit, 4chan, and Twitch containing potential misogynistic gaming discourse, alongside recruiting participants for interviews/focus groups with informed consent. After transcribing and anonymizing data, the initial qualitative phase analyzed 200 online texts using CDA frameworks (Fairclough/van Dijk) and interview/focus group transcripts using thematic analysis (managed with NVivo) to identify linguistic strategies, power dynamics, cognitive processes, and user experiences/impacts.

Based on these findings, the quantitative phase involved coding the 200 texts for predominant cognitive processes (Stereotyping/Prejudice, Social Categorization, Emotion) and platform origin, calculating frequencies, and performing a chi-square test to examine the association between cognitive processes and platforms.

Finally, a mixed-methods integration strategy synthesized the results, using quantitative data (frequencies, chi-square) to contextualize and add statistical weight to qualitative interpretations (e.g., the prevalence of strategies, platform differences), while qualitative insights helped explain quantitative patterns and understand impact/normalization. Ethical considerations, including review board approval, informed consent, and data anonymization, were maintained throughout the process.

 

3.6. Data Analysis

This study used CDA to examine online misogynistic trolling in the gaming community. Fairclough’s model and van Dijk’s discourse model were used to identify linguistic strategies and discursive devices in a corpus of 200 online texts to address the first research question. Qualitative findings identified patterns in the online misogynistic language and provided context to understand power dynamics and gender ideologies. For the second research question (cognitive processes), texts were categorized by predominant cognitive process (stereotyping, social categorization, emotional processes), and chi-square tests were used to bring to the surface any possible associations between these processes and specific online platforms. To address the third research question (impact on discourse), thematic analysis of interviews and focus groups with female gamers were utilized to look into their experiences, coping strategies, and the broader effects of online misogyny.

        4. Results

4.1. Results of the First Research Question

The first research question aimed to identify the linguistic strategies and discursive devices that are employed in online misogynistic discourse within the gaming community. To answer this research question, the researcher analyzed the corpus using Fairclough’s three-dimensional model and van Dijk’s discourse structure model.

Utilizing Fairclough’s framework uncovers multiple layers of hate speech and misogynistic trolling. Such being the case, at the discourse-as-text level, the researcher examined the linguistic features. The examples provided showcase a range of linguistic strategies, triggering misogynistic ideologies. These linguistic devices can be categorized under certain themes such as Sexual harassment (e.g., let’s 69, “send nudes,” “your ass looks like a Lamborghini in jeans,” “I’d love to get to know you better in private,” “you’re so beautiful, I just can’t help myself,” “you have a great body, you should show it off more,”), not only utilizes aggressive and emotionally charged vocabulary aiming to inflict psychological harm but also objectifies women and reduces them to their bodies. Besides, the frequent use of the terms such as “bitch”, “whore”, “slut”, and “cunt” are used to degrade and demean women, while Transphobic terms (e.g., tranny, shemale, he-she, it) are employed to marginalize and dehumanize transgender individuals.

The constellation of linguistic devices, representing misogynistic ideologies also unearths how power dynamics and gender ideologies manifest in the discourse surrounding online misogynistic trolling in the gaming community. The results brought to light that power dynamics and gender ideologies are deeply interwoven within the discourse surrounding online misogynistic trolling in the gaming community. In this connection, misogynistic language frequently employs objectification (e.g., send nudes), insults targeting women’s competence (“u only win coz ur a girl,” “U R a bimbo”), and threats of sexual violence (e.g., “I’ll have you gang-raped if you keep on bullshitting”). This language is not random; it is strategically deployed to assert dominance and control, reflecting a patriarchal power structure where women are seen as subordinate. The use of profanity and aggressive language further reinforces this power dynamic, creating an environment where women are intimidated into silence or submission.

The environment within which these texts are produced, circulated, and consumed provokes and strengthens the roots of patriarchal and misogynistic ideologies in gaming discourse. The online environment of gaming platforms facilitates anonymity and diffusion of responsibility, emboldening perpetrators. The rapid-fire nature of online communication allows for quick dissemination of hate speech and limits opportunities for reflection or rebuttal. The algorithms of these platforms can amplify hateful content, pushing it to wider audiences and creating echo chambers where such behavior is normalized or even celebrated. The interpretation of these messages depends on the background, ideologies, and power dynamics of both the sender and the receiver. Some comments (e.g., send nudes) might be interpreted as a simple request by some, but as a severe form of harassment by others. Racist terms (e.g., nigger, chink, gook, spic, wetback, Kike, raghead) are used to demean and dehumanize individuals based on their race or ethnicity. Ethnic slurs (e.g., honky, cracker, and redneck) further contribute to the divisiveness and hostility.

The very discursive status involves analyzing the broader societal implications, the prevalence of hate speech and misogynistic trolling reinforces existing gender inequalities and power imbalances within the gaming community, was observed. It contributes to a hostile online environment that discourages women from participating and perpetuates harmful stereotypes about female gamers. The normalization of such behavior through repetition and lack of effective moderation can have significant consequences for the well-being and safety of targeted individuals. The historical context of sexism and discrimination against women in general society plays a crucial role, in shaping the discourses and power dynamics observed online.

The pervasiveness of misogynistic trolling also reinforces broader societal gender ideologies. It perpetuates harmful stereotypes about women gamers (e.g., that they are unskilled, emotional, or only there for attention), discouraging female participation and reinforcing the idea that gaming is a male-dominated space. The normalization of such behavior contributes to a climate of fear and intimidation, impacting women’s confidence and ability to engage freely in online gaming communities. This aligns with Fairclough’s focus on how discourse reproduces and reinforces societal power structures. Moreover, van Dijk’s framework helps understand how cognitive processes and social representations contribute to the perpetuation of misogynistic hate speech:

Social Representations: Pre-existing gender stereotypes and ideologies are activated and reinforced through online hate speech. The discourse draws upon and reinforces the idea of women as inferior, hypersexualized, or emotionally unstable, justifying the targeting of women in online gaming spaces.

Group Identity and “Othering”: Hate speech often creates a clear distinction between an “in-group” (typically men) and an “out-group” (women). Women are positioned as the “other,” different, and less worthy of respect, leading to their dehumanization and targeted harassment.

Cognitive Schemas: The repeated exposure to misogynistic language and behavior shapes individuals’ cognitive schemas related to gender. This means that individuals who frequently encounter these messages gradually internalize and accept these sexist ideas, normalizing and perpetuating harmful attitudes.

Power and Control: The very act of online harassment is a manifestation of power. Perpetrators seek to assert dominance and control over women through their actions, reinforcing traditional power structures and gender norms.

Both Fairclough’s model and van Dijk’s socio-cognitive approach highlight how power dynamics and gender ideologies are not simply reflected in online hate speech but actively constructed and reinforced through it. The linguistic strategies, the online context, and the cognitive processes involved all contribute to the perpetuation of sexism and harassment within the gaming community. Addressing this complex issue requires challenging both the individual acts of hate speech and the deeper societal structures and beliefs that underpin them.

To gain a better understanding of the scope of these linguistic techniques and discursive mechanisms, quantitative analysis was undertaken to ascertain their frequency within the 200-item corpus. Analysis categorized identified misogynistic terms into broader themes, providing an overview of the occurrence of different types of online harassment. The analysis yielded the findings that language that was overtly misogynistic (i.e., in which at least one instance of derogatory language, sexual objectification, or threat toward women was present) was present in 65% (n = 130) of the texts analyzed. Table 1 presents the detailed breakdown by category.

Table 1

Frequency of General Categories of Misogynistic Language

Category	Frequency (n)	Percentage (%)
Derogatory Terms	110	55.0
Sexual Objectification	65	32.5
Threats	20	10.0
Transphobic Language	18	9.0

Table 1 shows that derogatory language was the most prevalent form of misogyny, accounting for 55% of the texts, followed by sexual objectification at 32.5%, indicating a trend of degrading women and treating them as sexual objects. Violent and sexual threats, though less frequent at 10%, highlighted the potential for online misogyny to escalate into real-world violence. Additionally, transphobic language, while least common at 9%, signaled discrimination against transgender individuals. Overall, the study demonstrates that online gaming is characterized by a multifaceted landscape of discriminatory and abusive discourse, creating a hostile environment that can have serious implications.

4.2. Results of the Second Research Question

The second research question was an attempt to pinpoint the cognitive processes and mental representations that facilitate the production and reception of online misogynistic discourse in the gaming community. This research question also sought to ascertain if there exists a statistically significant association between these cognitive processes and the specific online platforms on which this discourse occurs. Understanding the cognitive processes and mental representations underlying the production and reception of online hate speech and misogynistic trolling requires a well-established approach, drawing upon van Dijk’s (2008) socio-cognitive approach. Van Dijk’s model emphasizes the interplay between social context, cognitive processes, and the production and reception of discourse. In the context of online hate speech, several key cognitive processes are at play:

Stereotyping and Prejudice: Pre-existing negative stereotypes about women, minority groups, or other marginalized communities are activated and utilized to justify hateful actions. These stereotypes become readily accessible mental representations, influencing how individuals perceive and interact with others online. For example, a gamer holding a prejudiced belief that “women are bad at gaming” will more readily interpret a female player’s mistake as evidence of their inferiority, potentially triggering aggressive behavior.

Extract 1: Of course, she died first, what do u expect from a girl gamer? They should just play Candy Crush and not a competitive game.

Extract 2: All girls are here just for attention; they’re only good at support roles. I bet he’s in college just because of affirmative action. They never would have made it on merit alone.

The first comment relies on the negative stereotype that women are inherently less skilled at gaming, suggesting they are better suited for casual, less competitive games. It uses this prejudice to justify belittling and excluding female gamers. The second comment reveals a pre-existing stereotype influencing how the speaker perceives female gamers. The first extract activates negative stereotypes about the intellectual capabilities of minority groups, implying that their achievements are undeserved and solely due to affirmative action policies. It undermines their accomplishments and justifies discriminatory attitudes.

These examples demonstrate how pre-existing stereotypes and prejudices can be readily activated in online spaces, fueling hateful speech and discriminatory behavior toward women. Recognizing and challenging these harmful stereotypes is crucial in challenging the dominance of online misogynistic discourse in gaming environments.

Social Categorization and Group Identity: Individuals categorize themselves and Others into social groups, leading to in-group bias and out-group derogation. Online hate speech often reinforces these group boundaries, solidifying perceptions of “us” versus “them,” making it easier to dehumanize and attack members of the out-group. The “us” might be a group of gamers sharing a similar skill level or a particular gaming ideology; the “them” may be women in gaming, players of different genres, or players of different nationalities.

Extract 1: Women only get attention in gaming because they’re streamers, not because they’re skilled.

Extract 2: She probably only plays easy games.

In the above extracts, gender is the dividing factor, with male gamers identifying as the in-group and women as the out-group. This division fosters hostility and dehumanization, as women are seen not as equal participants but as outsiders who do not belong in the gaming space. Such rhetoric reinforces negative stereotypes about women’s abilities and contributions to gaming culture.

Emotional Processes: Anger, frustration, and resentment play a significant role. Negative emotions can be triggered by perceived unfairness or competition within online games. These emotions can then be channeled into hateful expressions online, providing a sense of catharsis or power for the perpetrator. For example, a player losing a match lashed out with misogynistic abuse towards a female player on the opposing team, projecting their anger onto her.

Extract 1: That girl is so bad; she ruined the game! I’m going to leverage her out and tell everyone how terrible she is.

Extract 2: She’s just a stupid bitch; she doesn’t deserve to be here.”

The first extract shows how frustration and anger can trigger aggressive behavior. The second excerpt reveals a process of dehumanization, where the victim is stripped of their humanity, making aggression easier to justify.

Cognitive Schemas: Pre-existing mental frameworks (schemas) about gaming culture, gender roles, and acceptable online behavior shape how individuals interpret and respond to online interactions. Individuals holding misogynistic schemas may interpret innocuous behaviors from female gamers as provocative or deserving of harassment.

Discourse Processing: Individuals do not passively absorb online misogyny; they actively process it. Factors such as the salience of the message (how attention-grabbing it is), the credibility of the source, and the individual’s pre-existing biases all influence how it is interpreted and whether it reinforces existing beliefs or leads to attitude change.

The production and reception of misogynistic trolling are complex phenomena shaped by a combination of individual cognitive processes, social group dynamics, and the affordances of the online environment. Understanding these cognitive mechanisms is crucial for developing effective strategies to combat this form of online harassment. This requires interventions targeting individuals’ prejudiced attitudes, fostering empathy and understanding, and creating online environments that minimize anonymity, increase accountability, and promote respectful behavior.

In order to statistically analyze the interaction between platform type and cognitive process, the researchers conducted a chi-square test. Every text in the corpus was tagged with the primary cognitive process it exhibited (Stereotyping/Prejudice, Social Categorization/Group Identity, or Emotional Processes). These tags were cross-tabulated with the platform on which the text was posted (Reddit, 4chan, Twitch). The resulting contingency table is as follows (Table 2).

Table 2

Cognitive Processes by Platform

Cognitive Process	Reddit (n)	4chan (n)	Twitch (n)	Total (n)
Stereotyping/Prejudice	25	35	15	75
Social Categorization	20	15	10	45
Emotional Processes	15	10	55	80
Total	60	60	80	200

Table 2 indicates a distinct pattern of cognitive processes among different online websites. 4chan experienced a higher prevalence of stereotyping and prejudice compared to other websites, and it may have a culture that makes it easier for existing biases to be expressed. Twitch was more associated with emotional processes, perhaps because of the more interactive and real-time nature of streaming communities where emotional behavior is readily expressed. While the pattern of social categorization was generally consistent across sites, these findings highlight how each site’s specific characteristics can influence the manifestation and reinforcement of specific cognitive processes associated with misogynistic behavior.

The chi-square test was conducted to determine if the association between the cognitive processes and the three platforms was significant (i.e., H0: There is no statistically significant association between cognitive processes and the type of platform, χ2(4, 200) = 25.27, p = 0.000 (p<0.05). Since the p-value (0.000) is less than the significance level (0.05), the null hypothesis is rejected and the alternative hypothesis is accepted. This p-value has surfaced a statistically significant association between cognitive processes and platform type. To identify which categories display significant differences, the adjusted residuals must be examined. Table 3 presents the adjusted standardized residuals.

Table 3

Adjusted Standardized Residuals for Cognitive Processes by Platform

Cognitive Process	Reddit	4chan	Twitch
Stereotyping/Prejudice	-0.57	3.42	-1.92
Social Categorization	0.68	0.11	-1.59
Emotional Processes	-0.11	-2.87	3.11

Note. p < .05 (two-tailed)

Table 3 illustrates a statistically significant relationship between some online platforms and some types of misogynistic expressions. The prevalence of prejudice/stereotyping is significantly more prevalent on 4chan than would be expected by chance (Adjusted Standardized Residual = 3.42, p <.05), but Twitch has a significantly higher prevalence of emotional processes (Adjusted Standardized Residual = 3.11, p <.05).

Based on these findings, 4chan displayed a stronger connection with stereotyping and prejudice expressions compared to the other platforms that were looked into. Twitch also demonstrated a stronger connection with emotional process expressions. This suggests that different online environments may support different types of misogynistic thought.

4.3. Results of the Third Research Question

The third research question was intended to understand how online misogynistic discourse in the gaming community shapes public discourse, attitudes, and potential normalization. Focus group discussions and interviews were conducted with female gamers to understand their experiences and coping strategies related to online hate speech and misogynistic trolling in the gaming community. The following themes emerged from the interviews:

4.3.1. Avoiding female avatars

Female gamers are aware that using female avatars can make them more vulnerable to negative comments, trolling, and sexist remarks. As a result, they consciously avoid using female avatars to minimize the risk of harassment and maintain a more enjoyable gaming experience.

Excerpt 1: I deliberately avoid using female avatars because it attracts negative comments and trolling.

Excerpt 2: Whenever I use a female avatar, I face more harassment and sexist remarks.

4.3.2. Trying to pass as a male

Some female gamers attempt to pass as male players by adopting masculine communication styles or avoiding voice chat. This strategy allows them to avoid being singled out and subjected to gender-based harassment, unwanted advances, and sexist comments.

Excerpt 1: I sometimes pretend to be a male player to avoid being singled out and harassed.

Excerpt 2: Passing as a male player helps me avoid unwanted advances and sexist comments.

 

4.3.3. Using gender-neutral avatar

Using gender-neutral avatars is a less common strategy employed by female gamers to avoid drawing attention to their gender. This approach enables them to focus on the game itself without being judged or harassed based on their gender identity.

Excerpt 1: I prefer using gender-neutral avatars to avoid drawing attention to my gender.

Excerpt 2: Gender-neutral avatars allow me to focus on the game without being judged based on my gender.

4.3.4. Using male username

Similar to using male avatars, female gamers adopt male-sounding user names to conceal their gender identity and avoid being identified as female gamers. This strategy helps them avoid unwanted attention and harassment that often comes with being recognized as a woman in the gaming community

Excerpt 1: I often choose a male-sounding user name to avoid being identified as a female gamer.

Excerpt 2: Using a male user name helps me avoid unwanted attention and harassment.

4.3.5. Using gender-neutral username

Gender-neutral user names provide female gamers with a sense of anonymity and help them avoid revealing their gender to other players. By maintaining a gender-neutral online presence, they can avoid attracting trolls and gender-based discrimination.

Excerpt 1: I opt for gender-neutral user names to avoid revealing my gender and attracting trolls.

Excerpt 2: Gender-neutral user names help me maintain anonymity and avoid gender-based discrimination.

4.3.6. Talking to someone about what happened

Seeking social support is a common coping strategy among female gamers who experience online hate speech and trolling. Talking to friends, family, or other trusted individuals about their experiences helps them process the emotional impact of harassment and find comfort in shared understanding.

Excerpt 1: When I face online hate speech or trolling, I reach out to friends or family for support.

Excerpt 2: Talking to someone about my experiences helps me cope with the emotional impact of harassment.

 

 

4.3.7. Asking other players for help

While less common, some female gamers reach out to other players for help when facing harassment. Asking fellow gamers to intervene can sometimes deter harassers and provide a sense of support and solidarity within the gaming community.

Excerpt 1: In some instances, I’ve asked other players to intervene when I was being harassed.

Excerpt 2: Seeking help from other players can sometimes deter harassers and provide a sense of support.

4.3.8. Telling the harasser directly it’s not okay

Some female gamers choose to confront their harassers directly, expressing that their behavior is unacceptable. While this approach can be empowering, it also carries the risk of escalating the situation and leading to further abuse.

Excerpt 1: I’ve confronted harassers directly, telling them their behavior is unacceptable.

Excerpt 2: Standing up to harassers can be empowering, but it can also lead to further abuse.

4.3.9. Reporting the harasser

Reporting harassers to game moderators or platform administrators is a formal way for female gamers to address the issue of online hate speech and trolling. This action helps hold perpetrators accountable for their actions and contributes to creating a safer gaming environment for all players.

Excerpt 1: I report harassers to the game moderators or platform administrators whenever possible.

Excerpt 2: Reporting harassers is important to hold them accountable and create a safer gaming environment.

4.3.10. Discussing the issue with someone outside the game 

Discussing experiences of online harassment with individuals outside the gaming community can provide female gamers with a different perspective and emotional support. This strategy allows them to process their experiences in a safe and understanding environment, separate from the gaming context.

Excerpt 1: I often discuss my experiences with online hate speech and trolling with friends outside the game.

Excerpt 2: Talking to someone outside the gaming community provides a different perspective and emotional support.

 

4.3.11. Discussing the issue with someone inside the game

Confiding in trusted gaming friends about experiences of harassment can be a source of comfort and validation for female gamers. Sharing their experiences with others who have faced similar situations creates a sense of solidarity and mutual understanding within the gaming community.

Excerpt 1: I sometimes confide in trusted gaming friends about the harassment I face.

Excerpt 2: Discussing with other players who have faced similar experiences can be comforting and validating.

4.3.12. Avoiding talking to others while playing

Some female gamers resort to avoiding communication with other players during gameplay as a preventive measure against harassment. By staying silent and focusing on the game, they aim to minimize unwanted attention and trolling, prioritizing their own gaming experience.

Excerpt 1: To minimize the risk of harassment, I often avoid communicating with other players during gameplay.

Excerpt 2: Staying silent and focusing on the game helps me avoid unwanted attention and trolling.

4.3.13. Leaving the game

In extreme cases, when the harassment becomes too overwhelming and other coping strategies prove ineffective, some female gamers choose to quit the game entirely. This drastic measure is often a last resort, highlighting the severe impact of online hate speech and trolling on their gaming experience.

Excerpt 1: When the harassment becomes too overwhelming, I sometimes quit the game entirely.

Excerpt 2: Leaving the game is a last resort when other coping strategies fail to address the issue.

4.3.14. Playing single player

Switching to single-player mode is a strategy employed by some female gamers to avoid interacting with potentially toxic players. Single-player games offer a haven where they can enjoy gaming without the risk of harassment, allowing them to have a more positive and uninterrupted gaming experience.

Excerpt 1: I often switch to single-player mode to avoid interacting with potentially toxic players.

Excerpt 2: Single player games provide a safe space where I can enjoy gaming without the risk of harassment.

 

 

4.3.15. Switching to a different lobby/server/match 

Switching to a different lobby, server, or match is a common coping strategy among female gamers when faced with harassment. By changing their gaming environment, they can escape the immediate situation and seek out a more welcoming and respectful space to continue playing.

Excerpt 1: When faced with harassment, I often switch to a different lobby, server, or match to avoid the perpetrators.

Excerpt 2: Changing the gaming environment helps me escape the immediate situation and find a more welcoming space.

4.3.16. Avoiding voice chat 

Avoiding voice chat is the most prevalent coping strategy among female gamers, as it allows them to conceal their gender and protect themselves from verbal harassment and sexist remarks. By refraining from using voice communication, they can maintain a degree of anonymity and reduce the likelihood of attracting unwanted attention based on their gender. 

Excerpt 1: I rarely use voice chat to avoid revealing my gender and attracting unwanted attention.

Excerpt 2: Avoiding voice chat is a precautionary measure to protect myself from verbal harassment and sexist remarks.

Table 4 illustrates the distribution of coping strategies reported by female gamers, throwing light on their responses to online harassment and toxicity. 

Table 4

Frequency of Coping Strategies among Female Gamers in Response to Online Misogyny

Coping Strategy	Frequency	Percentage
Avoiding female avatars	12	40.0
Trying to pass as a male	9	30.0
Using gender-neutral avatar	7	23.3
Using a male username	8	26.7
Using a gender-neutral username	6	20.0
Talking to someone about what happened	15	50.0
Asking other players for help	5	16.7
Telling the harasser directly it’s not okay	6	20.0
Reporting the harasser	10	33.3
Discussing the issue with someone outside the game	11	36.7
Discussing the issue with someone inside the game	13	43.3
Avoiding talking to others while playing	16	53.3
Leaving the game	4	13.3
Playing single player	6	20.0
Switching to a different lobby/server/match	9	30.0
Avoiding voice chat	20	66.7

Female gamers employ a range of coping strategies to navigate online misogyny, primarily focusing on gender concealment and minimizing interaction. Notably, 66.7% avoid voice chat, and over 40% skip female avatars, while 30% represent themselves as male, all to reduce harassment. Discussion-related and other avoidance strategies within the game were also common, reported by over 50% of participants, with leaving the game being the least used. These findings reveal that most female gamers feel compelled to alter their online presence and behavior to mitigate misogynistic treatment in gaming environments.

5. Discussion

This CDA examined misogynistic trolling within Reddit, 4chan, and Twitch gaming communities, revealing a significant presence of toxic behavior consistent with growing concerns about online hate speech (Fortuna & Nunes, 2018; Cao & Lee, 2020). Quantitative analysis related to the first research question indicated derogatory terms were most frequent (55%), followed by sexual objectification (32.5%), threats (10%), and transphobic language (9%), alongside other forms of hate speech. This prevalence reflects the problematic ways misogyny manifests, ranging from stereotyping and objectification to outright violence (Falsetti & Jackson, 1995).

Qualitative analysis, supported by frameworks from Fairclough and van Dijk, showed these linguistic strategies reinforce patriarchal ideologies and power dynamics, often subordinating women (Deng, 2024; Jagayat & Choma, 2021), aligning with observations about how power imbalances within gaming communities, sometimes linked to in-game status, can foster aggression (Zakaria et al., 2022). The anonymity afforded by these platforms (Fortuna & Nunes, 2018; Phillips, 2015) appears to exacerbate harassment by lowering accountability, thereby legitimizing exclusionary practices (Deng, 2024; Pira, 2015) within a field already marked by significant gender imbalance (De Palma, 2001; McKinney et al., 2008). Social identity theory (Tajfel & Turner, 1979) suggests this hate speech functions to strengthen in-group identity (often male gamers) by demeaning out-groups (female gamers), perpetuating the notion of gaming as a male domain (Ponterotto, 2014; Jakubowska, 2024).

Additionally, the research revealed a significant correlation between platform type and the cognitive processes driving misogynistic discourse, as investigated in the second research question. Stereotyping and prejudice were more common on 4chan, likely due to its less moderated, highly anonymous environment which facilitates aggression without consequence (Keya et al., 2023; Phillips, 2015), while emotional outbursts were more prevalent on Twitch, reflecting its real-time, high-stakes, interactive nature. This supports the notion that platform design and community norms significantly influence discourse (Ging et al., 2020), potentially amplifying existing societal biases (Koenig & Eagly, 2014) and creating echo chambers, particularly impactful given the younger demographic often susceptible to peer pressure (Marwick & Lewis, 2017; Sękowska-Kozłowska et al., 2022). The finding aligns with the under-researched area of cognitive mechanisms behind online hate production (ElSherief et al., 2018; Keya et al., 2023).

The qualitative findings concerning female gamers’ lived experiences and coping strategies (derived from the third research question) provide essential context and explanatory power for the quantitative data (from the first and second research questions). Specifically, the high frequencies of hostile language forms quantified in the findings for the first research question (e.g., 55% derogatory terms, 32.5% objectification) are directly explained by the participants’ widespread reliance on avoidance strategies reported in the findings for the third research question. For instance, the fact that 66.7% avoid voice chat and over 40% avoid female avatars represents a direct, adaptive response necessitated by the prevalence of the specific linguistic hostility measured quantitatively, reflecting attempts to navigate environments where women are frequently stereotyped as incompetent or merely decorative (Ponterotto, 2014; Sarkeesian, 2013). These coping mechanisms vividly illustrate how the statistically frequent misogynistic discourse translates into tangible fear – consistent with research suggesting links between online harassment and real-world harm or psychological distress (Lupu et al., 2023; Obermaier et al., 2023) – and requires significant behavioral modification for self-protection, underscoring the real-world impact of the quantitatively observed online toxicity. Furthermore, the finding from the second research question –different platforms foster different dominant cognitive processes (e.g., stereotyping on 4chan, emotional processes on Twitch) – helps account for the varied, though consistently negative, encounters gamers described based on the third research question’s findings. Their qualitative experiences of navigating environments characterized more by pervasive stereotyping (often rooted in broader societal biases, as discussed by Rollè et al., 2019 and Koenig & Eagly, 2014) versus those prone to sudden emotional outbursts are thus partly explained by the quantitative association found between platform type and cognitive patterns.

Integrating this study’s quantitative strands (findings related to the first research question’s frequencies, findings related to the second research question’s correlations) and qualitative strands (findings related to the third research question’s experiences) allows for several key meta-inferences. Firstly, the sheer frequency of specific misogynistic linguistic forms (identified in relation to the first research question), reflecting problematic gender representations seen in game content itself (Shaw, 2015; Downs & Smith, 2010; Dill & Thill, 2007), combined with the qualitative analysis of their strategic deployment and the profound impact described by targets (identified in relation to the third research question), suggests that online misogyny in these gaming spaces operates as a systemic discursive practice. This practice aims at enforcing gender hierarchies and controlling women’s presence, potentially achieving a level of normalization within these participatory online cultures (Phillips, 2015), thereby reinforcing limiting societal gender ideologies (Koenig & Eagly, 2014).

Secondly, the significant association between platform type and cognitive processes (identified in relation to the second research question), when viewed through the lens of CDA and user experiences (identified in relation to the third research question), implies that platform design and community norms are not neutral backdrops but actively contribute to shaping and amplifying particular forms of misogynistic expression. Platforms emphasizing anonymity like 4chan seem to cultivate prejudice-driven attacks (supported by data related to the second research question), potentially becoming breeding grounds for ‘networked misogyny’ (Ging et al., 2020), whereas highly interactive platforms like Twitch may facilitate more emotionally charged harassment (supported by data related to the second research question). This indicates platform structures are complicit in the nature and severity of the harm experienced (reflected in the findings related to the third research question), contributing to the cycle of exclusion described by Kowert et al. (2017).

Thirdly, connecting the quantitative language data (from the first research question) with the qualitative descriptions of coping mechanisms (from the third research question) reveals a meta-inference about the unequal distribution of burden: targets of misogyny are forced into considerable adaptive labor (i.e., identity management, interaction avoidance quantified in the findings for the third research question) as a direct consequence of the quantitatively measured linguistic hostility (identified via the first research question). This labor detracts from their participation and enjoyment, reinforcing their marginalization (Pira, 2015) and potentially deterring women from entering or staying in gaming or related IT fields (McKinney et al., 2008; Williams, 2014), perpetuating the hostile cycle.

6. Conclusions and Implications

In conclusion, online misogynistic trolling within the analyzed gaming communities represents a significant challenge affecting individual well-being and broader social equality, echoing concerns about online hate speech’s threat to social cohesion (Ghozali et al., 2023; Ștefăniță & Buf, 2021). Its pervasiveness, fueled by specific linguistic strategies, cognitive biases rooted in societal stereotypes (Wood & Eagly, 2002; Santoniccolo et al., 2023), and platform dynamics, necessitates the comprehensive interventions called for by researchers (Deligianni & Horne, 2023; Shruthi & Kumar, 2020; Wachs & Wright, 2018). These must target not only individual perpetrators but also the systemic issues within online platforms – including challenging the problematic representation of women in games (De la Torre Sierra & Guichot-Reina, 2024; Kennedy, 2002) and addressing toxic masculinity (Vallerga, & Zurbriggen, 2022) – to actively cultivate digital spaces that are respectful, equitable, and safe for all participants.

 

References

Burgess, M. C. R., Stermer, S. P., & Burgess, S. R. (2007). Sex, lies, and video games: The portrayal of male and female characters on video game covers. Sex Roles, 57(5–6), 419–433. https://doi.org/10.1007/s11199-007-9250-0

Cao, R., & Lee, R. (2020). HateGAN: Adversarial generative-based data augmentation for hate speech detection. Proceedings of the 28th International Conference on Computational Linguistics, 6327–6338. https://doi.org/10.18653/v1/2020.coling-main.557

Colder Carras, M., van Rooij, A. J., van de Mheen, D., Musci, R., Xue, Q. L., & Mendelson, T. (2017). Video gaming in a hyperconnected world: A cross-sectional study of heavy gaming, problematic gaming symptoms, and online socializing in adolescents. Computers in Human Behavior, 68, 472–479. https://doi.org/10.1016/j.chb.2016.11.060

Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). Sage publications.

De la Torre Sierra, A., & Guichot-Reina, V. (2024). Women in video games: An analysis of the biased representation of female characters in current video games. Sexuality & Culture, 28, 1–29. https://doi.org/10.1007/s12119-024-10286-0

De Palma, P. (2001). Viewpoint: Why women avoid computer science. Communications of the ACM, 44(6), 27–30. https://doi.org/10.1145/376134.376145

Deligianni, A., & Horne, Z. D. (2023). Analysing hate speech towards women on Reddit. PsyArXiv. https://doi.org/10.31234/osf.io/fsrq7

Deng, Z. (2024). “They don’t mean to hurt”: Female gamers’ reluctance in recognizing and confronting sexism in gaming as an online-offline juxtaposition. New Media & Society. Advance online publication. https://doi.org/10.1177/14614448241287831

Dill, K. E., Gentile, D. A., Richter, W. A., & Dill, J. C. (2005). Violence, Sex, Race, and Age in Popular Video Games: A Content Analysis. In E. Cole & J. H. Daniel (Eds.), Featuring females: Feminist analyses of media (pp. 115–130). American Psychological Association. https://doi.org/10.1037/11213-008

Dill, K. E., & Thill, K. P. (2007). Video game characters and the socialization of gender roles: Young people’s perceptions mirror sexist media depictions. Sex Roles, 57(11–12), 851–864. https://doi.org/10.1007/s11199-007-9278-1

Downs, E., & Smith, S. L. (2010). Keeping abreast of hypersexuality: A video game character content analysis. Sex Roles, 62(11–12), 721–733. https://doi.org/10.1007/s11199-009-9637-1

ElSherief, M., Nilizadeh, S., Nguyen, D., Vigna, G., & Belding, E. (2018). Peer to peer hate: Hate speech instigators and their targets. Proceedings of the International AAAI Conference on Web and Social Media, 12(1). https://ojs.aaai.org/index.php/ICWSM/article/view/15038

Fairclough, N. (1995). Critical discourse analysis: The critical study of language. Longman.

Fairclough, N. (2010). Critical discourse analysis: The critical study of language (2nd ed.). Routledge.

Falsetti, S. A., & Resnick, H. S. (1995). Helping the victims of violent crime. In J. R. Freedy & S. E. Hobfoll (Eds.), Traumatic stress: From theory to practice (pp. 263–285). Plenum Press.

Fortuna, P., & Nunes, S. (2018). A survey on automatic detection of hate speech in text. ACM Computing Surveys, 51(4), 1-30. https://doi.org/10.1145/3232676

Fox, J., & Bailenson, J. N. (2009). Virtual virgins and vamps: The effects of exposure to female characters’ sexualized appearance and gaze in an immersive virtual environment. Sex Roles, 61(3–4), 147–157. https://doi.org/10.1007/s11199-009-9599-3

Ghozali, I., Sungkono, K. R., Sarno, R., & Abdullah, R. (2023). Synonym based feature expansion for Indonesian hate speech detection. International Journal of Electrical and Computer Engineering, 13(1), 1105–1112. https://doi.org/10.11591/ijece.v13i1.pp1105-1112

Ging, D., Lynn, T., & Rosati, P. (2020). Neologising misogyny: Urban Dictionary’s folksonomies of sexual abuse. New Media & Society, 22(5), 838–856. https://doi.org/10.1177/1461444819870306

Heng, S., Zhao, H., & Wang, M. (2021). In-game social interaction and gaming disorder: A perspective from online social capital. Frontiers in Psychiatry, 11, Article 468115. https://doi.org/10.3389/fpsyt.2020.468115

Jakubowska, H. (2024). Who counts as a woman? A critical discourse analysis of petitions against the participation of transgender athletes in women’s sport. International Review for the Sociology of Sport, 59(2), 203–221. https://doi.org/10.1177/10126902231194570

Jagayat, A., & Choma, B. L. (2021). Cyber-aggression towards women: Measurement and psychological predictors in gaming communities. Computers in Human Behavior, 120, Article 106753. https://doi.org/10.1016/j.chb.2021.106753

Kay, A. C., Laurin, K., Fitzsimons, G. M., & Landau, M. J. (2014). A functional basis for structure-seeking: Exposure to structure promotes willingness to engage in motivated action. Journal of Experimental Psychology: General, 143(2), 486–491. https://doi.org/10.1037/a0034462

Keya, A. J., Kabir, M. M., Shammey, N. J., Mridha, M. F., Islam, M. R., & Watanabe, Y. (2023). G-BERT: An efficient method for identifying hate speech in Bengali texts on social media. IEEE Access, 11, 75873–75887. https://doi.org/10.1109/ACCESS.2023.3299021

Kennedy, H. W. (2002). Lara Croft: Feminist icon or cyberbimbo? On the limits of textual analysis. Game Studies: The International Journal of Computer Game Research, 2(2). http://www.gamestudies.org/0202/kennedy/

Koenig, A. M., & Eagly, A. H. (2014). Evidence for the social role theory of stereotype content: Observations of groups’ roles shape stereotypes. Journal of Personality and Social Psychology, 107(3), 371–392. https://doi.org/10.1037/a0037215

Kowert, R., Breuer, J., & Quandt, T. (2017). Women are from FarmVille, men are from ViceCity: The cycle of exclusion and sexism in video game content and culture. In R. Kowert & T. Quandt (Eds.), New perspectives on the social aspects of digital gaming: Multiplayer 2 (pp. 104–120). Routledge. https://doi.org/10.4324/9781315629308-9

Lupu, Y., Sear, R., Velásquez, N., Leahy, R., Restrepo, N. J., Goldberg, B., & Johnson, N. F. (2023). Offline events and online hate. PLoS ONE, 18(1), Article e0278511. https://doi.org/10.1371/journal.pone.0278511

Marwick, A. E., & Lewis, R. (2017). Media manipulation and disinformation online. Data & Society Research Institute. https://datasociety.net/pubs/oh/DataAndSociety_MediaManipulationAndDisinformationOnline.pdf

McKinney, V., Wilson, D., Brooks, N., O’Leary-Kelly, A., & Hardgrave, B. (2008). Women and men in the IT profession. Communications of the ACM, 51(2), 81–84. https://doi.org/10.1145/1314215.1314229

Mulvey, L. (1999). Visual pleasure and narrative cinema. In L. Braudy & M. Cohen (Eds.), Film theory and criticism: Introductory readings (5th ed., pp. 833–844). Oxford University Press.

Obermaier, M., Schmid, U. K., & Rieger, D. (2023). Too civil to care? How online hate speech against different social groups affects bystander intervention. European Journal of Criminology, 20(3), 817–833. https://doi.org/10.1177/14773708231156328

Phillips, W. (2015). This is why we can’t have nice things: Mapping the relationship between online trolling and mainstream culture. MIT Press.

Pira, A. (2015). Misogyny in the world of online gaming? A critical discourse analysis about how female gamers are portrayed in the Swedish Media [Unpublished master’s thesis]. Lund University.

Ponterotto, D. (2014). Trivializing the female body: A cross-cultural analysis of the representation of women in sports journalism. Journal of International Women’s Studies, 15(2), 94–111. https://vc.bridgew.edu/jiws/vol15/iss2/7

Potter, W. J. (2022). Analysis of definitions of media literacy. Journal of Media Literacy Education, 14(2), 27–43. https://doi.org/10.23860/JMLE-2022-14-2-3

Rollè, L., Ramon, S., & Brustia, P. (2019). Editorial: New perspectives on domestic violence: From research to intervention. Frontiers in Psychology, 10, Article 641. https://doi.org/10.3389/fpsyg.2019.00641

Salminen, J., Luotolahti, J., Almerekhi, H., Jansen, B. J., & Jung, S.-G. (2018). Neural network hate deletion: Developing a machine learning model to eliminate hate from online comments. In A. Voiskounsky, O. Smirnova, & A. Ershov (Eds.), Digital Transformation and Global Society. DTGS 2018. Communications in Computer and Information Science (Vol. 859, pp. 24–36). Springer. https://doi.org/10.1007/978-3-030-01437-7_3

Santoniccolo, F., Trombetta, T., Paradiso, M. N., & Rollè, L. (2023). Gender and media representations: A review of the literature on gender stereotypes, objectification and sexualization. International Journal of Environmental Research and Public Health, 20(10), Article 5770. https://doi.org/10.3390/ijerph20105770

Sarkeesian, A. (2013, March 7). Damsel in distress: Part 1 — Tropes vs women in video games [Video]. YouTube. https://www.youtube.com/watch?v=X6p5AZp7r_Q

Sękowska-Kozłowska, K., Baranowska, G., & Gliszczyńska-Grabias, A. (2022). Sexist hate speech and the international human rights law: Towards legal recognition of the phenomenon by the United Nations and the Council of Europe. International Journal for the Semiotics of Law - Revue internationale de Sémiotique juridique, 35(3), 1017–1039. https://doi.org/10.1007/s11196-022-09884-8

Shaw, A. (2015). Gaming at the edge: Sexuality and gender at the margins of gamer culture. University of Minnesota Press. https://doi.org/10.5749/minnesota/9780816693153.001.0001

Shruthi, P., & Kumar, A. K. M. (2020). Novel approach for generating hybrid features set to effectively identify hate speech. Inteligencia Artificial, 23(66), 97–111. https://doi.org/10.4114/intartif.vol23iss66pp97-111

Ștefăniță, O., & Buf, D.-M. (2021). Hate speech in social media and its effects on the LGBT community: A review of the current research. Romanian Journal of Communication and Public Relations, 23(1), 47–55. https://doi.org/10.21018/rjcpr.2021.1.322

Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In W. G. Austin & S. Worchel (Eds.), The social psychology of intergroup relations (pp. 33–47). Brooks/Cole.

Vallerga, M., & Zurbriggen, E. L. (2022). Hegemonic masculinities in the ‘Manosphere’: A thematic analysis of beliefs about men and women on The Red Pill and Incel. Analyses of Social Issues and Public Policy, 22(2), 602–625. https://doi.org/10.1111/asap.12308

Van Dijk, T. A. (1988). News analysis: Case studies of international and national news in the press. Lawrence Erlbaum Associates.

Van Dijk, T. A. (2008). Discourse and context: A sociocognitive approach. Cambridge University Press.

Wachs, S., & Wright, M. F. (2018). Associations between bystanders and perpetrators of online hate: The moderating role of toxic online disinhibition. International Journal of Environmental Research and Public Health, 15(9), Article 2030. https://doi.org/10.3390/ijerph15092030

Walsh, A., & Leaper, C. (2020). A content analysis of gender representations in preschool children’s television. Mass Communication and Society, 23(3), 331–355. https://doi.org/10.1080/15205436.2019.1664593

Williams, G. (2014). Are you sure your software is gender-neutral? Interactions, 21(2), 36–39. https://doi.org/10.1145/2524808

Williams, M. L., Burnap, P., Javed, A., Liu, H., & Ozalp, S. (2020). Hate in the machine: Anti-Black and anti-Muslim social media posts as predictors of offline racially and religiously aggravated crime. The British Journal of Criminology, 60(1), 93–117. https://doi.org/10.1093/bjc/azz049

Wood, W., & Eagly, A. H. (2002). A cross-cultural analysis of the behavior of women and men: Implications for the origins of sex differences. Psychological Bulletin, 128(5), 699–727. https://doi.org/10.1037/0033-2909.128.5.699

Zakaria, M., Ali, A., & Abdul Aziz, A. (2022). Online gaming: Exploratory of the communication process and current scenario of virtual community development. International Journal of Academic Research in Business and Social Sciences, 12(11), 827–842. https://doi.org/10.6007/IJARBSS/v12-i11/14739

 

 

 

(Received: 11/03/2025; Received in revised form: 12/04/2025; Accepted:13/04/2025; Published online: 26/5/2025)

© The Author(s), 2024.          Article type: Research Article                    Publisher: Qom Islamic Azad University