Data mining of Twitter posts can help identify when people become sympathetic to groups like ISIS

Researchers have shown that data mining techniques can be used to understand when Twitter users start displaying supportive behaviour to radical terror groups such as ISIS. Analysis of 154,000 Europe-based Twitter accounts and more than 104 million tweets (in English and Arabic) relating to Syria show that users of the social media platform are more likely to adopt pro-ISIS language - and therefore display potential signs of radicalisation - when connected to other Twitter users who are linked to many of the same accounts and share and retweet similar information. The research, which has been done in close collaboration between Lancaster University and the Open University, is explained in the paper 'Mining pro-ISIS radicalisation signals from social media users'. The research provides evidence that shows when users begin either sharing tweets from known pro-ISIS accounts, or using extremist language - such as anti-western or pro-ISIS statements - they quickly display a large change in the language they use, tweeting new words and terms, and indicating a clear shift in online behaviour. Often before a user shows signals of having become radicalised they discuss topics such as politics, using words such as Syria, Israel and Egypt in a negative context and highly frequently. However, once they display signals of radicalisation their language changes to use religious words more frequently, such as Allah, Muslims and Quran, it was found. Dr Matthew Rowe, Lecturer at Lancaster University's School of Computing and , said: "We found that social dynamics play a strong role where Twitter users are more likely to adopt pro-ISIS language from other users with whom they have a lot of shared connections.