This article focuses on the problem of identifying influential Twitter users using Machine Learning (ML) techniques and Natural Language Processing (NLP).
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 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 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.
This article studied a selection of right-wing extremist (RWE) groups on Twitter. The authors looked at particular language-based networks as case studies, collecting Twitter data for groups across eight countries.
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