识别暗网论坛中的派系——一种聚集聚类方法

Tarique Anwar, M. Abulaish
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引用次数: 21

摘要

本文提出了一种新的聚类方法来识别暗网论坛中的派系。考虑到每个帖子都是一个单独的实体,包含有关其线程、作者、时间戳等的所有信息,我们定义了一个相似性函数来识别每对帖子之间的相似性,作为其上下文和时间一致性的混合。本文提出的聚类算法利用相似度函数将线程分组到不同的聚类中,这些聚类最终被表示为单独的团。已识别的派系使用其中的帖子的同质性来表征,这也建立了其作者和线程的同质性。
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Identifying cliques in dark web forums - An agglomerative clustering approach
In this paper, we present a novel agglomerative clustering method to identify cliques in dark Web forums. Considering each post as an individual entity accompanying all the information about its thread, author, time-stamp, etc., we have defined a similarity function to identify similarity between each pair of posts as a blend of their contextual and temporal coherence. The similarity function is employed in the proposed clustering algorithm to group threads into different clusters that are finally presented as individual cliques. The identified cliques are characterized using the homogeneity of posts therein, which also establishes the homogeneity of their authors and threads as well.
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