This paper discusses automated methods for detecting online radicalization and radical communities on various platforms, from websites, to forums, to social media platforms such as Facebook, YouTube, Twitter, and others.
This paper explores the use of crawling global social networking platforms to undercover previously unknown radicalized individuals. To prove the utility of this process the authors collect a YouTube dataset from a group that potentially has a radicalizing agenda.
This 2013 article analyzes content generated on Twitter during the attacks at the Boston Marathon in April 2013. The authors perform an in-depth characterization of what factors influenced malicious content and profiles becoming viral.
This 2013 paper describes Netvizz, a data collection and extraction application on Facebook that allows researchers to export data in standard file formats from different sections of the social networking platform.
This 2012 paper develops a novel methodology for modeling cyber-collective social networks (CSMs) from individual, community, and transnational perspectives. The authors do this by utilizing existing collective action theories and computational approaches for social network analysis.
This 2014 paper utilizes a form of network representation that incorporates multiple data views to uncover and categorize networks of accounts that fall into four broadly defined groups in the Syrian conflict.
This netnographic study examines al-Shabaab’s Western media strategy. The authors focus their study on the group’s recruitment of Western Muslims through the analysis of primary sources, interviews in East Africa and a quantitative analysis of the group’s Twitter outputs.
The article aims to build an unsupervised model to estimate relationship strength based on profile similarity and interaction activity.
This portal gathers an annotated collection of recent research on the ways in which social media and new technologies may be leveraged in the fight against violent extremism