基于ERGM和LDA的暗网论坛极值内聚评价

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2019-08-01 DOI:10.1145/3341161.3343532

Mohammed Rashed, J. Piorkowski, I. McCulloh

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引用次数: 3

摘要

ISIS和类似的极端主义社区越来越多地利用暗网论坛相互联系，传播新闻和宣传。在本文中，我们试图通过描述性统计，指数随机图模型(ERGM)和主题建模来理解他们在在线论坛中的网络。我们的分析显示了活跃成员之间的凝聚力是如何随着时间的推移和在特定的线程主题下形成和增长的。我们发现，论坛的顶级参与者具有较高的中心性度量和影响者的其他属性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Evaluation of Extremist Cohesion in a Darknet Forum Using ERGM and LDA

ISIS and similar extremist communities are increasingly using forums in the darknet to connect with each other and spread news and propaganda. In this paper, we attempt to understand their network in an online forum by using descriptive statistics, an exponential random graph model (ERGM) and Topic Modeling. Our analysis shows how the cohesion between active members forms and grows over time and under certain thread topics. We find that the top attendants of the forum have high centrality measures and other attributes of influencers.

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来源期刊

2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

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