Socio-Semantic Network Analysis for Extremist and Terrorist Online Ecosystems
Year: 2025
Type: article
Abstract: How to best chart and analyse extremist digital ecosystems? This paper proposes to complement standard mapping methods based on URL outlinks, which are typically deployed but present several critical flaws, with socio-semantic network analysis. Adapting bi-nodal socio-semantic network principles to the specificities of extremist and terrorist digital communications, we put forward a simple yet efficient method for generating informative networks based on ideological or thematic proximity rather than URL connections. We use three datasets of various sizes and nature (French far-right websites, British far-right websites, US far-right Telegram channels) to compare traditional URL-based vs. socio-semantic networks, demonstrating how the latter bypasses the flaws of the former and offers significant advantages in multi-methods research designs. This empirical validation of our methodological proposition unfolds several new observations concerning the contemporary Western far-right digital ecosystem, highlighting specificities and commonalities of its French, British, and American variants.
Authors: Stephane J. Baele, Lewys Brace
Institutions: UCLouvain, KU Leuven, University of Exeter
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Funder: Horizon 2020
Award: G696119916
OpenAlex ID: W4408772484