Extracting radicalisation behavioural patterns from social network data


Social networks (SNs) have become essential communication tools in recent years, generating a large amount of information about its users that can be analysed with data processing algorithms. Recently, a new type of SN user has emerged: jihadists that use SNs as a tool to recruit new militants and share their propaganda. In this paper, we study a set of indicators to assess the risk of radicalisation of a social network user. These radicalisation indicators help law-enforcement agencies, prosecutors and organizations devoted to fight terrorism to detect vulnerable targets even before the radicalisation process is completed. Moreover, these indicators are the first steps towards a software tool to gather, represent, pre-process and analyse behavioural indicators of radicalisation in terrorism.

2017 28textsuperscriptth International Workshop on Database and Expert Systems Applications (DEXA)
Antonio Gonzalez-Pardo
Antonio Gonzalez-Pardo
PhD Computer Science

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.