NOTIONES paper about the EC-funded research for fighting terrorist narratives

NOTIONES is proud to present a new dissemination paper about the EC-funded research for fighting terrorist narratives. This paper descends from task T4.2 of NOTIONES and is authored by consortium partners Zanasi & Partners and Expert.AI.

The paper reports on the EC-funded research to study and fight terrorist narratives, considering the outputs of the EC-funded research projects – and the analysis techniques implemented in those projects – retrieved from the Community Research and Development Information Service (CORDIS) portal. Projects dedicated specifically to terrorist narratives and counternarratives were investigated in detail, among those funded by the EU’s framework programmes for research and innovation (FP1 to Horizon 2020) as well as the European Research Council (ERC) and Internal Security Fund Police (ISFP) frameworks.

A summary of the main results is provided in the paper by means of an overview of the main terrorist narratives, considering information and data emerged from the review of selected research projects, enriched with general literature review.  Five terrorist narratives are addressed: a) Jihadist violent extremist narratives, b) Right-wing violent extremist narratives, c) Left-wing and anarchist violent extremist narratives, d) Ethnonationalist and Separatist violent extremist narratives; e) Single issue-terrorism violent extremist narratives (e.g. animal rights, environmental terrorism, etc.).

Details are also provided for the most widely used analytical technique, e.g. semantic analysis of terrorist narratives disseminated online. The review attempts to build an informational bridge providing the research know-how to the pan-European network of Security and Intelligence practitioners, so that the collected information can be translated into practical recommendations, technologies and tools enabling practitioners to perform their duty against terrorism in an enhanced, optimized and more efficient manner.

The paper is also available on Zenodo: https://zenodo.org/record/7740401#.ZCKgWfZBxD8