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Political Polarization Mechanics on Persian Twitter (X): A Social Network Analysis of the 2024 Iranian Presidential Election | ||
| Journal of Cyberspace Studies | ||
| مقاله 9، دوره 9، شماره 1، فروردین 2025، صفحه 175-201 اصل مقاله (1.15 M) | ||
| نوع مقاله: Original article | ||
| شناسه دیجیتال (DOI): 10.22059/jcss.2025.388449.1122 | ||
| نویسندگان | ||
| Mahshid Shahidi1؛ Hossein Hassani* 2؛ Marzieh Haddady3 | ||
| 1Department of Economic Sociology and Development, Science and Research Branch, Islamic Azad University, Tehran, Iran. | ||
| 2Department of Cyberspace Studies, Communication Research Institute, Research Institute for Culture, Art, and Communication, Tehran, Iran. | ||
| 3Artificial Intelligence, Azad University of Karaj, Iran. | ||
| چکیده | ||
| Background: The 2024 Iranian presidential election intensified political polarization on Persian Twitter (X), where ideological factions engaged in networked contestation. This study employs social network analysis to examine polarization mechanics, mapping key actors, echo chambers, and discursive strategies. Findings illuminate digital factionalism, algorithmic amplification, and the role of influencers in political mobilization. Aims: This study explores the mechanisms driving political polarization on Persian Twitter (X) during the 2024 Iranian presidential election. Methodology: Utilizing computational social science methodologies, the research combines social network analysis (SNA) and thematic analysis to examine over 133,000 active users and numerous election-related hashtags. Data collection spanned June 1–16, 2024, leveraging Twitter's API to identify clusters, user interactions, and thematic trends. Key tools included the Louvain algorithm for community detection and centrality measures for network analysis, visualized through Gephi software. Findings: Findings reveal a fragmented political landscape characterized by ideological divides, echo chambers, and limited interaction between opposing factions. Analysis identified six major clusters, each aligned with distinct political affiliations, including reformists, conservatives, and opposition groups. Thematic analysis further highlighted the rhetoric surrounding leading candidates Masoud Pezeshkian and Saeed Jalili, revealing polarized sentiments and distinct narratives among their supporters and detractors. The study also underscores the role of platform algorithms, influencer strategies, and group identities in deepening polarization. Conclusions: This research contributes to the understanding of digital polarization within Iran's socio-political context. It emphasizes the dual role of social media as both a space for public discourse and a driver of ideological segregation. Recommendations include strategies for promoting digital literacy, fostering inclusive discussions, and enhancing algorithmic transparency to mitigate polarization in Iran. | ||
| کلیدواژهها | ||
| echo chambers؛ political polarization؛ persian Twitter؛ social network analysis؛ 2024 Iranian presidential election | ||
| مراجع | ||
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