Temporal dynamics of coordinated online behavior: Stability, archetypes, and influence

• 成果类型: Article
• 署名作者: Tardelli, Serena; Nizzoli, Leonardo; Tesconi, Maurizio; Conti, Mauro; Nakov, Preslav; Martino, Giovanni Da San; Cresci, Stefano
• 署名单位: Consiglio Nazionale delle Ricerche (CNR); University of Padua; Mohamed bin Zayed University of Artificial Intelligence MBZUAI
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-15388
• DOI: 10.1073/pnas.2307038121
• 发表日期: 2024-05-14
• 关键词: multiscale

摘要

Large-scale online campaigns, malicious or otherwise, require a significant degree of coordination among participants, which sparked interest in the study of coordinated online behavior . State-of-the-art methods for detecting coordinated behavior perform static analyses, disregarding the temporal dynamics of coordination. Here, we carry out a dynamic analysis of coordinated behavior. To reach our goal, we build a multiplex temporal network and we perform dynamic community detection to identify groups of users that exhibited coordinated behaviors in time. We find that i) coordinated communities (CCs) feature variable degrees of temporal instability; ii) dynamic analyses are needed to account for such instability, and results of static analyses can be unreliable and scarcely representative of unstable communities; iii) some users exhibit distinct archetypal behaviors that have important practical implications; iv) content and network characteristics contribute to explaining why users leave and join CCs. Our results demonstrate the advantages of dynamic analyses and open up new directions of research on the unfolding of online debates, on the strategies of CCs, and on the patterns of online influence.