Jihadist groups such as ISIS are spreading online propaganda using various forms of social media such as Twitter and YouTube. One of the most common approaches to stop these groups is to suspend accounts that spread propaganda when they are discovered. This approach requires that human analysts manually read and analyze an enormous amount of information on social media. In this work we make a first attempt to automatically detect messages released by jihadist groups on Twitter. We use a machine learning approach that classifies a tweet as containing material that is supporting jihadists groups or not. Even tough our results are preliminary and more tests needs to be carried out we believe that results indicate that an automated approach to aid analysts in their work with detecting radical content on social media is a promising way forward. It should be noted that an automatic approach to detect radical content should only be used as a support tool for human analysts in their work.
['Michael Ashcroft', 'Ali Fisher', 'Lisa Kaati', 'Enghin Omer', 'Nico Prucha']
Detecting Jihadist Messages on Twitter