Semantic Analysis Supporting De-Radicalisation

Abstract

Internet and Social media are widely used by terrorist organizations to spread their ideas and recruit foreign fighters. The aim of SAFFRON is to build a system able to support early detection of foreign fighters' recruitment by terrorist groups in Europe. It consists in studying recruitment communication strategies on social media (e.g. narrations, argumentative tropes and myths used), and their evolution in time, as well as in identifying needs, values, cultural and social contexts of the target groups (young foreign fighters). In this paper, we will describe SafApp, the application we have developed to support semantic analysis of social network with a particular focus on how SAFFRON makes use of natural language processing and machine learning to categorize and analyse content of messages dealing with recruitment and radicalization on social networks.

Detection of Radicalisation and Extremism Online: A Survey

“…), with specific terms or indicators. Later the systems are trained on the vocabulary and apply it to get the desired results, e.g., [47]. Since the vocabulary is defined or designed for a specific context or data is collected for a particular language, the approach cannot efficiently be utilised in other languages.…”