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This study investigates how political discourse spreads across social media by identifying influential user groups, termed focal structures. We construct a cross-platform multiplex network linking users and narratives, and apply the Contextual Focal Structures Analysis (CFSA) algorithm to detect context-specific influence. Focusing on Taiwan’s 2024 presidential election, we analyze 4,817 Instagram, 2,560 TikTok, 11,134 X, and 7,327 YouTube posts. Our findings reveal that influence often stems not from individuals but from coordinated or organically aligned groups shaping narratives across platforms. This work presents a scalable method for modeling narrative-driven influence, highlighting the importance of understanding cross-platform coordination in shaping political perceptions.

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Analysis of Cross-Platform Narrative Dissemination Through Contextual Focal Structures

  • 会议论文

  • 发表日期：

    2026年

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  • Ridwan Amure,
  • Nitin Agarwal

摘要

This study investigates how political discourse spreads across social media by identifying influential user groups, termed focal structures. We construct a cross-platform multiplex network linking users and narratives, and apply the Contextual Focal Structures Analysis (CFSA) algorithm to detect context-specific influence. Focusing on Taiwan’s 2024 presidential election, we analyze 4,817 Instagram, 2,560 TikTok, 11,134 X, and 7,327 YouTube posts. Our findings reveal that influence often stems not from individuals but from coordinated or organically aligned groups shaping narratives across platforms. This work presents a scalable method for modeling narrative-driven influence, highlighting the importance of understanding cross-platform coordination in shaping political perceptions.