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 article focuses on the use of linguistic “weak signals”—digital traces of intent—in social media as a tool of counterterrorism aimed at preventing lone-wolf attacks.
The authors of this article propose a methodology for automatically identifying events and their associated user-contributed social media documents (such as those posted on Flickr, YouTube, and Facebook) to enable event browsing and search in state-of-the-art search engines.
This paper examines approaches for analyzing Twitter messages to distinguish between those covering real-world events and non-event messages. To validate this work the authors applied their process to 2.6 million Twitter messages.
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