Exploring structural features of terrorist organization's online supporting community via social network modeling

With the strengthening of the offline strike together with the booming development of the Internet platform, terrorist organizations have increased their online activities. In general, as a breeding ground, online supporting community has been adopted by terrorist organizations to stimulate their activities. Thus, exploring the structural features of terrorist organizations' social networks is of great importance for intelligence acquisition and online intervention. In this paper, Social Network Analysis (SNA) was used to analyze the structural features of the online supporting community of a specific terrorist organization (denoted as X) to obtain the main structural features. Specifically, after the networks established, we first measured the centrality and prestige of the members in the online community. Results revealed that the betweenness centrality was the most effective method to find the key members for online community. Second, for the small group phenomenon, we divided the cluster subgroup with four different methods. Results indicated that the 3-cores degree-based method can best reflect the core structure of the online community. Third, we simplified the online community to form a better yet simplified network. Finally, we compared online community with four typical network structures, and found that its structure has higher cohesion and vitality.