Alumdadini Bilqis Lanisari
Data Science Department, Universitas Pembangunan Nasional Veteran Jawa Timur, Surabaya, Indonesia

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Multidimensional Analysis of Hashtag-Driven Conversations: Detecting Hybrid Discourse Patterns in the #KaburAjaDulu Twitter Campaign Andri Fauzan Adziima; Wahyu SJ Saputra; Windri Saifudin; Meisya Vira Amelia; Alumdadini Bilqis Lanisari
International Journal of Social Science and Business Vol. 10 No. 1 (2026): February
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ijssb.v10i1.105807

Abstract

This study investigated the multidimensional dynamics of the Indonesian hashtag #KaburAjaDulu on Twitter (X) between April and July 2025. By integrating sentiment analysis, social network analysis (SNA), and topic modeling, the research developed a framework to distinguish organic grassroots discourse from coordinated non-organic amplification, often associated with "buzzer" activity. Findings revealed that conversation volume peaked in May and July 2025, largely dominated by positive sentiment. The SNA identified a complex network structure that was simultaneously decentralized and characterized by dense clusters indicative of coordinated behavior. Key actors with high centrality scores functioned as both popular figures and essential information bridges. Topic modeling indicated that positive discourse centered on humor, personal success, and lighthearted narratives, while negative sentiment consistently aligned with themes of national skepticism and career frustration. The integration of these methodologies demonstrated that the #KaburAjaDulu phenomenon was shaped by a multifaceted interplay of trending narratives and influential actors. The study concluded by providing a practical analytical framework for social media and policy research, enabling stakeholders to monitor public discourse and map influential actors to inform evidence-based responses to emerging societal issues.