Initially founded by the New York-based social activist Tarana Burke in 2006, #MeToo aimed to empower women and support victims of sexual assaults in the United States. A decade later, the movement gained worldwide attention when actress Alyssa Milano popularized #MeToo with a viral Twitter (subsequently rebranded X) trend. The movement broadened awareness while reflecting the emotional strain tied to large-scale public disclosure [1,2]. From a public health perspective, this increase represents more than social awareness. It reflects large-scale digital expressions of trauma that reveal population-level exposure to gender-based violence (GBV) and related mental health consequences [3-5].

Gender equality movements such as #MeToo are often viewed as women-led initiatives [6], which shapes how people engage with them online. This framing also explains why public responses became sharply divided or polarized. Expressions of solidarity promoted healing and collective efficacy [5,7,8], while hostile or dismissive comments reproduced stigma and secondary victimization [9]. Prior analyses have shown that discussions around #MeToo contained both destructive elements, such as ridicule, rape references, and scandal language, and constructive ones emphasizing education, leadership, and rights [5,9]. Such polarization is health-relevant because antagonistic discourse can intensify psychological distress, discourage help-seeking, and perpetuate unsafe disclosure climates for survivors [3,10-12]. Opponents of #MeToo viewed the movement as threatening social identity and existing hierarchies [13,14], further sustaining online environments that can undermine survivor well-being and collective healing.

In this context, while the #MeToo movement resonated worldwide, its impact on the Indian Entertainment Industry (IEI), particularly Bollywood, was notably profound, serving as a catalyst that broke long-standing barriers of silence within the entertainment sector [15]. Within the IEI, disclosures emerged rapidly and publicly, revealing deep-seated gender hierarchies and power asymmetries that had long silenced survivors. For instance, late Bollywood choreographer Saroj Khan remarked, “Bollywood provides bread, at least doesn’t abandon women after rape” in the wake of the #MeToo movement in India [16]. Such comments exemplify how public figures can normalize or excuse sexual violence, reflecting the cultural narratives that sustain institutional denial and perpetuate psychological harm for survivors [17]. These justifications and dismissive reactions have measurable health implications. Studies show that negative or invalidating responses to #MeToo disclosures are associated with increased posttraumatic stress, anxiety, and feelings of isolation among survivors [18,19].

In the Indian context, such backlash often manifests through public shaming, social exclusion, and reputational damage, creating conditions of secondary victimization that discourage reporting [17,20,21]. Although social media facilitates visibility and mobilization, it also amplifies exposure to stigma and retraumatization, turning disclosure spaces into sites of both empowerment and psychological risk [1]. Thus, our analysis addresses calls to understand the system-justification narratives within #MeToo that reproduce structural inequities and generate secondary mental health burdens for survivors [9,19,22].

Alongside social and moral support, #MeTooIndia also generated negative reactions in the form of backlash, victim blaming, and social system justification [23]. In patriarchal contexts, women survivors often face reputational risks and moral scrutiny that discourage disclosure and silence voices of resistance [20,24]. Backlash also stemmed from a perception that #MeTooIndia threatened group identity and the existing social order, prompting many to defend traditional hierarchies through system-justifying narratives [25,26]. Previous research on #MeToo links disbelief and ridicule following disclosure to trauma recurrence, anxiety, and avoidance behaviors [9,10,22]. This study examines online reactions to #MeToo through the lens of a digital health discourse. Social-media discourse surrounding GBV functions not only as a forum for advocacy but also as a public-health signal that reflects collective trauma and emotional distress [4,18]. Such digital expressions can inform health care providers, mental health professionals, and public health practitioners about emerging patterns of psychosocial stress and the need for trauma-informed care and community-level interventions [27,28].

We treat the justification narratives surrounding #MeToo as infoveillance indicators, which are digital signals of GBV and secondary victimization addressing limitations identified in prior research [5,29]. Hostile or invalidating comments constitute secondary victimization [30,31], which research links to increased posttraumatic stress, anxiety, and social withdrawal among survivors [9,11,19,22]. Within patriarchal or celebrity-dominated contexts such as India’s entertainment industry, such backlash can reinforce stigma and reproduce structural inequities that exacerbate mental health burden [17,20]. Positioning the analysis within this digital-health framing enables examination of how social-media environments impact both public-health awareness and secondary psychological harm following GBV disclosure [3].

Social conditioning often creates circumstances in which seeking justice can, unfortunately, intensify the harassment experienced by victims [5,22,37]. Secondary victimization occurs through social media when the perpetrators face legal problems, and the community unjustly holds the victim responsible [38,39]. System justification theory suggests that “there is a general ideological motive to justify the existing social order,” and this motive is responsible for the “internalization of inferiority among the members of the disadvantaged group” [40]. System justification theory has been applied across disciplines, including public health, using established scales to assess how individuals endorse or legitimize existing social systems [41,42]. An example of a belief measure is the view that society is structured so that people generally get what they deserve. It is important to distinguish psychological system justification, which reflects unconscious cognitive motives to legitimize existing hierarchies, from strategic or systemic resistance, which involves deliberate actions by individuals or institutions to preserve power and resist reform [43,44].

System justifiers create a fear of judgment or retaliation for sexual victims, drastically reducing the disclosure [19,45,46]. A substantial number of tweets criticized individuals, including prominent figures, who had blamed victims of sexual harassment for their experiences, thereby undermining the feminist movement [22,47]. The inclination to rationalize current social structures may be particularly strong in the context of gender dynamics compared with other intergroup settings, such as racial, religious, or ethnic groups, as gender relations are deeply interdependent within social and economic systems [25]. The types of system justifications are listed in Table 1.

Similarly, investigating the 2017 Women’s March movement, researchers found that mostly in the case of men (who identify gender as less important to one’s self-concept), exposure to gender movement increased system justification tendency [48]. Furthermore, men who expressed support for gender system justification believed that #MeToo unjustly tarnished the reputation of men. Evidence indicates that the endorsement of sexist ideologies is connected to individuals’ perspectives on sexual harassment and their stance toward the #MeToo movement [50].

While defending the existing gender system may represent the main narrative for system justification within such movements, it is not the only type represented on social media. Reports have highlighted the limited accountability of businesses and institutions during the #MeToo movement [51]. Sociocultural and organizational systems often reinforce beliefs and behaviors that perpetuate sexual harassment and misconduct. Furthermore, victims bear the personal cost of legal representation, while institutions support the defense of powerful offenders. Such dynamics contribute to secondary victimization and institutional retaliation, maintained through system-justifying mechanisms [52].

Witnessing online victimization has been shown to promote dehumanization of victims, leading to perceptions that they are less deserving of respect or protection [21,53]. Such cognitive and emotional distancing contributes to harmful social norms that normalize violence and reduce collective empathy, which are both recognized as public health concerns [10,19]. Victim-blaming justifications are produced when individuals experience identity threats and defensively protect their self-image by partially or fully attributing blame to the victim [5,18]. These justifications are reinforced by gender-powered dynamics and male sexual aggression, which in turn increase women’s vulnerability and sustain beliefs rationalizing the just world hypothesis [53-55].

Victim-blaming justifications not only shift attribution away from perpetrators but also contribute to resistance against the broader goals of the #MeToo movement. This form of discourse often frames the movement as an overreaction or a threat to individual freedom, thereby undermining efforts to address GBV and promote safer social environments [5,17]. Such responses reflect a broader tendency to preserve positive perceptions of existing social systems, even when these systems sustain inequities that have significant public health implications for victims’ mental and physical well-being [19,29,49]. Earlier research indicates that the movement could provoke even more intense negative responses from those who are unsympathetic or hold contrary beliefs about its objectives [5,36,48].

Understanding how systems justify and reproduce themselves is key to identifying the social and psychological barriers that impede collective action. From a public health perspective, such insights can guide targeted strategies to disrupt these barriers, strengthen community engagement, and sustain online activism that promotes equity and safety.

The global #MeToo movement revealed significant regional variation in engagement and public discourse [35,56]. Recognizing that social movements addressing GBV have broad implications for population health and social well-being, we adopted a mixed-methods design to examine how digital narratives reinforce or challenge systemic inequities. This study comprised two components: (1) a quantitative analysis of tweets to assess the global diffusion and framing of #MeToo via social media, and (2) a qualitative study using in-depth interviews focused on #MeTooIndia to contextualize the movement’s local impacts.

This research used a sequential explanatory mixed-methods design in which study 1 directly informed study 2 [57]. The quantitative analysis of Twitter discourse identified 4 dominant forms of system justification, and these empirically derived categories guided the development of the semistructured interview guide (Multimedia Appendix 1). Study 2 was therefore designed to contextualize, elaborate, and extend the patterns observed in study 1 by examining how similar justification mechanisms were understood within the localized context of the IEI. During interpretation, findings from both studies were integrated to provide a consolidated understanding of how digital narratives and institutional responses interact during #MeToo.

In the first study, we collected tweets without geographic restrictions to minimize sampling bias and capture cross-cultural expressions of system justification. Regional and cultural contexts can shape how individuals legitimize or contest social hierarchies online, influencing public perceptions of gender justice and safety—key determinants of health equity. Guided by system justification theory, which posits that individuals tend to rationalize and defend existing social structures even when they sustain inequality, we used natural language processing–based topic classification to identify patterns of justification within global #MeToo discussions. We then complemented these findings with an in-depth case study of #MeTooIndia, drawing on expert interviews to explore how these justifications manifest within the Indian sociocultural and institutional context, which led to our second study.

In our second study, we examined the social and behavioral consequences of the #MeTooIndia movement within the context of IEI. Prior research underscores that diverse cultural settings can obscure interpretation unless analyzed within a specific context [58]. IEI, particularly Bollywood, offered a compelling case as the movement gained strong momentum, generated widespread public engagement, and empowered women actors to voice experiences of sexual misconduct. To capture these dynamics, we conducted interviews with research scholars specializing in media or film studies to gain nuanced insight into the social and institutional responses surrounding #MeTooIndia.

While the 2 studies used different methods, they collectively offer a multidimensional understanding of digital activism and its societal implications. The natural language processing–based analysis in study 1 captures large-scale public discourse and patterns of system justification, whereas the expert interviews in study 2 provide contextual depth and interpretation of those narratives. Together, these complementary approaches offer a more comprehensive view of how such digital feminist movements intersect with cultural norms, institutional accountability, and collective well-being. Consistent with Gorissen et al [22], who found that Twitter hosted 61.4% of sexual victimization disclosures during #MeToo, our focus on Twitter data ensured a consistent and extensive dataset for examining system-justifying narratives that influence public attitudes toward gender equity and safety.

The processed data supporting our conclusions, along with the Python (Python Software Foundation) syntax required for reproducing the results, can be obtained from the authors upon request. All analyses were performed using Python libraries. Please note that this study’s design and analysis were not preregistered because the research was exploratory and aimed at developing theoretical and methodological insights rather than testing predefined hypotheses (Figure 1).

For quantitative study 1, all data were obtained from publicly accessible sources on Twitter. Posts shared under the hashtags (#MeToo and #metoo) represent public communications intended for open audiences. No personal or identifying information about individual users (such as usernames, user IDs, or direct mentions) was retained, as all data were deidentified before analysis. All analyses were conducted on aggregated text data, focusing on linguistic and thematic patterns rather than individual users or specific tweets. Results are therefore presented in group form to ensure that no inferences can be made about any specific user. Given ongoing concerns about the potential for reidentification of social media users, even when direct identifiers are removed, we took additional precautions when presenting illustrative material (sample tweets). All sample content used for explanation in this paper was paraphrased, and any original handles were replaced with neutral placeholders to prevent traceability. Finally, while we do not publicly share any of the analyzed data, we outline more details in the “Data Availability” section [59,60].

For study 2, all participants were experienced academics familiar with research ethics and the principles of informed consent and institutional review. Each received an information sheet describing this study’s objectives, procedures, and data-use policy. Participation was voluntary. Participants were interviewed strictly in their professional capacity, and no identifiable personal data was collected. The authors analyzed qualitative materials that were recorded in a fully anonymized form. This study did not involve interaction or intervention beyond the collection of anonymous responses. Accordingly, the work met criteria for minimal-risk social research and did not constitute human participants research requiring institutional review board oversight under the US Common Rule (45 CFR §46.102) [61]. Additionally, the research adhered to the ethical principles of the Declaration of Helsinki [62] and the World Health Organization’s (2001) guidelines for ethical qualitative inquiry [63].

To protect privacy and confidentiality, all interviews were conducted and recorded in English with explicit participant consent. Transcripts were deidentified, assigned numeric codes, and stored on password-protected devices accessible only to the research team. No identifiable information, images, or supplementary materials are included in this paper. Participation was entirely voluntary, and no monetary compensation was provided. Table 2 summarizes the demographic characteristics of the scholars and experts who participated in this study.

Gender system justification emerged as the most prevalent category, representing 37% of the dataset and reflecting discourse that reinforces established gender hierarchies and traditional gender norms. Institutional system justification accounted for 40% (7366/18,416), characterized by narratives that defend organizational practices or minimize institutional accountability in cases of harassment and misconduct. Smaller yet meaningful proportions included backlash system justification (2026/18,416, 11%) and victim-blaming system justification (2210/18,416, 12%), illustrating persistent efforts to discredit the #MeToo movement or to shift responsibility onto victims. Together, these findings provide a quantitative overview of how online conversations reproduce societal power structures that sustain gender-based inequities—factors with significant implications for public health, safety, and psychosocial well-being.

The distribution captures the relative prevalence of each justification type, offering a data-driven perspective on the broader discourse surrounding gender justice and institutional accountability. Thus, study 1 offers a global quantitative map of justification narratives, while study 2 qualitatively examines these dynamics within #MeTooIndia in the IEI, illustrating how cultural norms and institutional structures shape experiences, responses, and barriers to gender equity and collective well-being.

This study examined how social media discourse surrounding the #MeToo movement reflects and reproduces system-justifying narratives related to GBV. Consistent with this study’s objectives, the analysis identified 4 dominant forms of system justification—gender, institutional, victim-blaming, and backlash—across a large corpus of Twitter data and expert interviews. Study 1 demonstrated that online conversations frequently defended existing gender norms and institutional structures, with gender and institutional justification emerging as the most prevalent categories. Such defense mechanisms reflect social conditioning, resistance to change, and selective exposure to congruent beliefs online [81,82].

Study 2 further contextualized these patterns within the IEI, revealing that even as #MeTooIndia expanded public dialogue on sexual harassment—entrenched hierarchies, reputational risks, and institutional inertia continued to constrain meaningful reform. Together, these findings indicate that while the #MeToo movement fostered visibility and collective awareness, digital spaces also became arenas where system-justifying discourse reinforced social inequities and psychological strain, consistent with prior work showing that exposure to gender movements can amplify defensive reactions [48,50].

From a public health standpoint, these polarization patterns have psychosocial implications. Online gender-justifying narratives perpetuate stigma, discourage disclosure of sexual harassment, and increase survivors’ emotional distress [10,19]. The normalization of inequitable discourse can further sustain hostile digital climates that contribute to secondary victimization—a public health concern linked to trauma recurrence and barriers to help-seeking [22,38]. The high prevalence of institutional justification observed in the dataset also reflects persistent trust in existing social and institutional structures, even when those systems perpetuate inequality [20,21,29]. System justification fulfills a psychological need to defend and justify existing social arrangements, even if those are disadvantageous to society, as it is often perceived as psychologically comforting to individuals [40].

Institutional justification in feminist movements often works to preserve the status quo, especially when current arrangements benefit those in power [36,49]. These dynamics help explain why movements such as #MeToo can expose systemic issues and yet still fall short of durable institutional change. Finally, victim blaming and backlash justifications appeared less frequently but remained consequential. While victim-blaming and backlash in feminist movements have been widely examined [21,29,32,83,84], our findings show a comparatively lower prevalence of such narratives in the #MeToo discourse on social media. The wide circulation of survivor stories helped render overt victim-blaming less acceptable, reshaping public perceptions of sexual harassment and assault [5,33]. However, amplifying women’s voices through #MeToo also led some men to perceive themselves as unfairly victimized, fueling backlash that reasserted traditional gender hierarchies [20,85].

The “#MeTooLate Effect,” where delayed disclosures prompted disbelief or blame, underscores persistent biases that privilege certain forms of reporting [21,54]. Perceived credibility often follows a hierarchy shaped by social expectations of an “ideal” victim (such as immediate reporting or corroborating witnesses), thereby marginalizing survivors who do not conform to these norms [11,86]. Overall, these findings suggest that while social media amplifies awareness of GBV, it also functions as a mirror of societal polarization. This simultaneously promotes empowerment and entrenches opposition. Thus, digital backlash can increase psychological distress, inhibit help-seeking, and perpetuate stigma surrounding GBV [3,11,19]. Addressing these online narratives through trauma-informed communication, digital moderation, and survivor-centered discourse strategies is essential for promoting mental well-being and social equity.

The #MeToo movement in India catalyzed multiple discourses, revealing both systemic awareness and persistent structural inequities within the IEI [87,88]. Insights from study 2, based on in-depth interviews with scholarly experts, highlighted the movement’s mixed legacy—while it expanded public dialogue around sexual harassment, entrenched gender hierarchies and institutional practices remained largely unchanged [15,89]. This disconnect between awareness and reform mirrors broader societal resistance to redistributing power within patriarchal systems [87,90].

Participants described continuing patterns of victim blaming toward women who disclosed harassment, often amplified by media sensationalism. Such reactions perpetuate psychological distress, reputational harm, and social isolation, underscoring how hostile cultural responses can evolve into public health concerns through cumulative mental health and occupational stress [91,92]. Experts noted that survivors in high-visibility professions face compounded stigma and scrutiny, exacerbating trauma and discouraging disclosure. This outcome is consistent with global research on secondary victimization [22,38].

Interviewees also identified a persistent paradox in the IEI’s engagement with #MeToo, where increased public messaging on gender equity coexists with limited organizational accountability. This tension illustrates a symbolic commitment to feminist ideals rather than substantive institutional reform. Several experts described the movement’s momentum as short-lived “clicktivism” or “slacktivism,” characterized by digital enthusiasm but little lasting sociolegal impact [93-95]. Participants further noted that sustained solidarity was essential for continued engagement and resistance to social silencing, consistent with theories of collective action [96], though public disclosure frequently came with substantial psychological and professional costs.

Celebrities who spoke out faced coordinated online harassment, smear campaigns by industry elites, and defamation lawsuits aimed at intimidating or silencing them [16,89]. Such backlash reinforces patriarchal power structures and contributes to chronic distress, anxiety, and social withdrawal among women in high-visibility professions [20,92]. The hostile digital environment surrounding #MeTooIndia thus serves as an infoveillance signal of ongoing GBV and secondary victimization, illustrating how digital spaces can perpetuate trauma even while exposing it.

Despite these tensions, participants viewed the movement’s visibility as crucial for advancing public dialogue on sexual violence and strengthening institutional accountability. Achieving digital health and safety requires trauma-informed legal frameworks and industry mechanisms that protect survivors and translate online advocacy into sustainable, health-promoting reform. These findings should be interpreted alongside the limitations described in the next section.

Several key limitations influence the strength of the conclusions and recommendations drawn from this study. First, study 1 analyzed tweets collected over 1 month between November and December 2017, shortly after the initial #MeToo surge. This captures the early phase of the movement but may not represent later shifts in framing. Second, only English-language tweets were included, excluding parallel conversations in regional languages. Third, study 2 relied on 20 in-depth interviews with scholars and researchers specializing in gender, media, and film studies, constraining the analysis to the IEI context. While these experts provided valuable theoretical and contextual nuance, the perspectives of survivors (who experience digital hostility and secondary victimization directly) may differ in important ways. The absence of survivor interviews represents an additional limitation. Additionally, cultural norms, linguistic variations, and platform-specific affordances may have shaped the tone and visibility of #MeToo discourse, limiting the generalizability of findings across social and regional contexts.

This study examined how social media discourse within the #MeToo movement reflects system-justifying narratives that sustain rather than dismantle existing hierarchies [5]. Contrary to prior studies emphasizing victim-blaming and overt backlash, findings from both study 1 and study 2 reveal strong evidence of gender and institutional system justification. These patterns indicate that social media often reinforces traditional gender norms and institutional authority, maintaining the status quo even within digital spaces that appear progressive. Although #MeToo expanded visibility and awareness, its ability to drive enduring structural change within sectors such as the IEI remains limited. Digital platforms, therefore, operate as contested arenas, where technologies that enable collective voice can simultaneously reproduce digital GBV.

Our findings extend scholarship that centers primarily on backlash and victim-blaming by demonstrating how broader system-justifying frames appear in social media discourses. The findings carry 3 major implications. First, for digital platforms, they highlight the need for proactive governance and content moderation policies that curb system-justifying retaliatory discourse. This requires integrating trauma-informed design principles to reduce secondary victimization. Second, for public health and policy stakeholders, the results point to the importance of recognizing digital hostility as a psychosocial health risk that warrants coordinated mental health and legal interventions. Third, for researchers and feminist advocates, this work offers an analytic lens for situating digital activism within broader institutional and psychological systems, while identifying points where transformative change may stall.