RiskTrack: a new approach for risk assessment of radicalisation based on social media data

Abstract

The RiskTrack project aims to help in the prevention of terrorism through the identi cation of online radicalisation. In line with the European Union priorities in this matter, this project has been designed to identify and tackle the indicators that raise a red ag about which individuals or communities are being radicalised and recruited to commit violent acts of terrorism. Therefore, the main goals of this project will be twofold: On the one hand, it is needed to identify the main features and characteristics that can be used to evaluate a risk situation, to do that a risk assessment methodology studying how to detect signs of radicalisation (e.g., use of language, behavioural patterns in social networks…) will be designed. On the other hand, these features will be tested and analysed using advanced data mining methods, knowledge representation (semantic and ontology engineering) and multilingual technologies. The innovative aspect of this project is to not offer just a methodology on risk assessment, but also a tool that is build based on this methodology, so that the prosecutors, judges, law enforcement and other actors can obtain a short term tangible results.

Antonio Gonzalez-Pardo

Associate Professor

Lecturer at the Computer Science Department. Main research interests are related to Computational Intelligence and Metaheuristics applied to Social Networks Analysis, and the optimization of graph-based problems.