EMOTIONAL VIRALITY AND FRAGMENTED DIGITAL CULTURE: A COMPUTATIONAL ANALYSIS OF THE #INDONESIAGELAP DISCOURSE

Abstract

This study examines the dynamics of digital activism within the #IndonesiaGelap discourse by focusing on the interplay between virality, emotion, and narrative structure in shaping the quality of public participation. Moving beyond the dominant online–offline dichotomy, this study argues that the limitations of digital activism are not solely rooted in its failure to translate into offline mobilization, but also in the internal weaknesses of digital discourse itself. Employing a qualitative digital discourse analysis supported by big data analytics, this research analyzes cross-platform social media conversations during February 2025. The findings reveal that high levels of virality are not accompanied by sustained public attention, but instead produce intense yet short-lived engagement patterns. Although the term “Indonesia Gelap” emerges as a dominant umbrella label, the narrative structure remains highly fragmented, with low cohesion across competing sub-issues. In terms of symbolic representation, the absence of a consistent symbolic anchor prevents the formation of a unified collective identity, reducing the discourse to an aggregation of issues rather than a coordinated movement. Furthermore, participation is predominantly characterized by low-risk activism, as indicated by the dominance of retweet-based interactions, limited deliberative engagement, and strong dependence on momentum-driven attention cycles. This pattern suggests that digital participation functions more as content amplification than as collective meaning-making. Conceptually, this study extends the “many clicks but little sticks” framework by demonstrating that the limitations of digital activism also stem from the inability of digital discourse to develop narrative cohesion, symbolic consistency, and sustained engagement. These findings highlight that virality alone is insufficient to produce meaningful movement consolidation within social media ecosystems.