<![CDATA[Cases of sexual violence frequently exposed on social media have sparked intense discussions among digital citizens. This phenomenon has given rise to new patterns of participation in the digital public sphere, indicating progress in efficiently and effectively expressing public aspirations through online civic engagement. Thus, online citizen engagement further strengthens the concept of digital citizenship as an active participation form in the digital world. In this study, the topic modeling method is utilized as a machine learning approach with statistical methods to identify topics within large, unstructured document collections. The applied topic modeling method is Latent Dirichlet Allocation (LDA), using data collected from Twitter through crawling big data using the Twitter API. The results of this research reveal the discourse on sexual violence discussed by citizens with seven topics, namely: 1) Indonesia's sexual violence emergency; 2) Support for the enactment of the Draft Law on the Prevention of Sexual Violence, opposing parties against the Draft Law on the Prevention of Sexual Violence; 3) Pros and cons of Minister of Education and Culture and Research and Technology Regulation No. 30 of 2021 concerning the Prevention and Handling of Sexual Violence in Higher Education; 4) Sexual violence as sadistic behavior; 5) Sexual violence on campuses and in Islamic boarding schools; 6) Support for Minister of Education and Culture and Research and Technology Regulation No. 30 of 2021 for the prevention and handling of sexual violence on campuses; and 7) Stop sexual violence against children and women. From the analysis of the topic modeling results, it is evident that with a good understanding of citizen engagement facilitated by technology, the younger generation can develop digital citizenship in the practice of online civic engagement.]]>
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