Abstract
This study investigates how AI-generated political content on TikTok operates as a subaltern counterpublic within Indonesia’s polarized media environment. The research explores how marginalized or dissenting users employ digital platforms to craft counterdiscourses that challenge state narratives, articulate political grievances, and contest dominant interpretations of governance. The purpose of the study is to understand how these AI-enabled multimodal practices function as arenas for both collective withdrawal and public agitation, expanding spaces for political expression beyond the constraints of traditional media. A dataset of 200 TikTok videos produced with VEO 3 was analyzed using multimodal critical discourse analysis combined with a linguistic framework of discursive blaming strategies. The analysis systematically identified how users express political critique through negative judgments of capacity and propriety, implicit or invoked evaluations, and behavior-focused blame. The findings show a strong emphasis on criticizing governmental behavior, particularly around corruption, broken promises, and administrative failures. Sarcasm, symbolic imagery, and other affective multimodal cues further strengthened the oppositional tone of these videos. The study demonstrates that AI-generated political content can intensify the expressive capacity of digital counterpublics, enabling users to navigate platform constraints while producing pointed critiques of state authority. At the same time, the findings highlight the ambivalent nature of social media in polarized contexts: these platforms can reinforce ideological divides but also serve as crucial spaces for democratic resilience when mainstream channels are constrained. Overall, the research underscores the growing role of AI-enabled multimodal discourse in shaping contemporary political contestation and grassroots resistance in Indonesia.
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
AI-Generated Content, Counterpublics, Multimodal Discourse, Political Blaming, TikTok Politics
