<![CDATA[This research analyzes misogynistic comments on Emma Watson’s Instagram posts using Critical Discourse Analysis, focusing on posts related to sexual harassment and women in STEM from January 1st and 3rd, 2022. Employing Fairclough’s three-dimensional framework, the study examines 14 selected comments at textual, discursive, and social practice levels, applying Moloney & Love’s (2018) categorization framework of superiority-based, oppression-based, and stigma-based misogyny. The selection focused on two specific posts from January 1st and 3rd, 2022, chosen for their direct engagement with feminist topics that typically attract significant misogynistic responses on visual-centric platforms where image-text interactions create unique harassment dynamics. The findings reveal a relatively even distribution of misogynistic discourse types: superiority-based misogyny (35.71%), oppression-based misogyny (35.71%), and stigma-based misogyny (28.57%). Superiority-based comments utilized pseudo-scientific arguments and biological determinism to naturalize gender inequalities, particularly in STEM fields. Oppression-based comments actively attempted to silence Watson's feminist advocacy through aggressive role enforcement and professional delegitimization. Stigma-based comments deployed character assassination, stereotyping, and intersectional discrimination to undermine feminist messaging. The analysis reveals sophisticated patterns of digital misogyny that extend beyond individual harassment to represent systematic efforts to maintain gender hierarchies through linguistic intimidation. Comments frequently exploited Watson’s celebrity status to question her intellectual authority, demonstrating how public figures advocating for gender equality face intensified scrutiny designed to discourage continued activism. The research contributes to understanding how visual-centric platforms like Instagram create unique manifestations of gender-based harassment and offers important implications for digital governance, content moderation policies, and feminist media studies. These findings have direct implications for social media platform governance, suggesting the need for more sophisticated content moderation algorithms that can detect subtle linguistic patterns of systematic harassment beyond explicit hate speech.]]>
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