Real-Time Detection of Violence and Extremism from Social Media.
Funded by the Engineering and Physical Sciences Research Council (EPSRC).

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The proposed research describes a new approach to detecting trends of violent radicalization and extremism in social media. In particular, it proposes a Bayesian modeling approach which identifies violent contents in social media without the use of any labeled 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" which is 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 from the proposed research are potentially very important to society as they aim to enable the timely deployment of the forces of law to prevent violent events.

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