The Bot Amplification Paradox: How Algorithmic Bots Subvert Crisis Agenda-Setting

Building on Zhang et al.'s (2024) finding that social bots lead public agendas in elections and Wang & Wang's (2024) work on Zelenskyy's crisis communication, this research examines bots' role in non-electoral crises (e.g., conflicts, disasters). While agenda-setting theory assumes media leads the public, bots may hijack this process by flooding platforms with synthetic content. Using machine learning to detect bots and sentiment analysis, we’d track agenda dynamics during real-time crises (e.g., Ukraine, Sudan). This challenges Einarsson et al.'s (2024) focus on news recommender systems by revealing agenda-setting driven not by algorithms but malicious actors. The innovation lies in quantifying how bots create "false first-level agendas" that force media/public to react, reversing the traditional media→public flow.

References:

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