Real-Time Detection of Violence and Extremism from Social Media

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The explosive use of social media tools in recent years has turned them into a double-edged sword. On one hand, social media is viewed as a positive factor in Middle East revolutions. On the other hand, violence events such as the UK riots occurred in August this year appeared to be driven by the use of social media. The proposed project represents a timely development of intelligent systems for addressing the emerging defense and security issues arising from social media.The proposed research describes a new approach to detecting trends of violent radicalization and extremism from social media. In particular, it proposes a Bayesian modeling approach which detects violence contents from social media without the use of any labelled data. Words indicating violence, anger, hate, racism, etc. are naturally incorporated as prior knowledge into the model learning process. Efficient online parameter updating and parallel data processing procedures will be investigated. This proposal falls into the area of "Extracting meaningful information" listed in the original call for proposals. It particularly aims to tackle the technical challenge of real-time processing of large-scale social media data for early detection of violent extremism from text. The results of the research are potentially very important to society as they aim to enable the deployment of the forces of law to prevent violent events.