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Community detection in large networks is a process that has been heavily researched in the past decade due to the the emergence of online social networks. For Twitter, Inc., analyzing terrorists communities is vital in the fight against ISIS recruiters who use the twitter platform to radicalize people around the world. The goal of this project is to develop an algorithm which can accurately detect communities in large networks and to provide textual analysis on the discovered communities. Our algorithm combines the results of two unsupervised clustering algorithms to find communities in a given network. One algorithm uses the structure of the network, and the other algorithm uses the text associated with the nodes. Our algorithm is tested on a hand labeled ground truth twitter network and applied to an ISIS twitter recruiting network.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Kelly, Patrick Michael, "Community Detection for Counter-Terrorism" (2017). Senior Projects Spring 2017. 361.