触发：对极端主义团体环境影响的统计分析
Triggered: A Statistical Analysis of Environmental Influences on Extremist Groups
AI总结：
本文通过分析极端主义论坛与主流社区的数据，揭示了极端主义团体对现实事件和新闻报道的反应差异，以及语言扩散和行为动态的变化。
摘要：
在线极端主义社区存在于由现实事件、新闻报道和跨社区互动塑造的更广泛信息生态系统中。我们采用系统视角，利用来自两个意识形态不同的极端论坛（Stormfront和Incel）和一个主流参考社区（r/News）的七年数据，来研究这些影响。我们提出了三个问题：极端暴力如何影响社区行为；新闻报道是否预测了政治实体的对话动态变化；以及主流和极端空间之间，以及极端意识形态之间的语言扩散是否发生。方法上，我们结合反事实合成来估计事件层面的影响，以及向量自回归和格兰杰因果分析来建模新闻信号、行为结果和跨社区语言变化之间的持续关系。在分析中，我们的结果表明，Stormfront和r/News似乎对外部刺激更敏感，而Incel则表现出较少的跨社区语言影响和较少的对新闻和暴力事件的反应。这些发现强调，极端主义社区并不同质，它们在与周围信息生态系统耦合的紧密程度上有所不同。
英文摘要：
Online extremist communities operate within a wider information ecosystem shaped by real-world events, news coverage, and cross-community interaction. We adopt a systems perspective to examine these influences using seven years of data from two ideologically distinct extremist forums (Stormfront and Incels) and a mainstream reference community (r/News). We ask three questions: how extremist violence impacts community behaviour; whether news coverage of political entities predicts shifts in conversation dynamics; and whether linguistic diffusion occurs between mainstream and extremist spaces and across extremist ideologies. Methodologically, we combine counterfactual synthesis to estimate event-level impacts with vector autoregression and Granger causality analyses to model ongoing relationships among news signals, behavioural outcomes, and cross-community language change. Across analyses, our results indicate that Stormfront and r/News appear to be more reactive to external stimuli, while Incels demonstrates less cross-community linguistic influence and less responsiveness to news and violent events. These findings underscore that extremist communities are not homogeneous, but differ in how tightly they are coupled to the surrounding information ecosystem.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
