Many covert and terror groups have a strong presence in social media. ISIS, in particular, is well known for its use of social media. The group's ability to proliferate its message using unaffiliated social media users has proven to be an powerful element of their resourcing strategy and is already being immitated by other similar groups like Jabhat al-Nusra. The ability of threat groups to cultivate and utilize large online communities of passive supporters is likely here until we develop effective methods to combat them. Although community detection and covert network detection methods offer methods to identify these groups they often lack the precision required to use them operationally or do not provide the computational scalability to detect these relatively small groups embedded in large social networks. To effectively combat these threat group supporting online communities requires new methodologies to detect them and identify key users and roles.
This repository is a companion to the PLOS ONE Submission 'Threat Group Detection in Social Media: Uncovering the ISIS Supporting Network on Twitter' by Matthew Benigni, Kenny Joseph, and Kathleen M Carley. The R scripts provide all the functions neccessary to recreate our work, and we have provided de-identified edge lists for users available at The CASOS Covert Network Project.