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Originalarbeit

Big Data in der Radikalisierungsforschung

Eine systematische Übersichtsarbeit

Published Online:April 27, 2020https://doi.org/10.1026/0033-3042/a000480

Abstract

Zusammenfassung. Die Erforschung extremistischer Radikalisierung hat durch digitale Verhaltensspurdaten, wie z. B. Social-Media-Posts oder öffentlich zugänglichen Medien, einen neuen Auftrieb erfahren. Vor dem Hintergrund, dass Big Data als „epistemologische Revolution“ angesehen wird, liefert die vorliegende systematische Literaturübersicht einen Überblick darüber, (i) welche Ziele, Datenquellen und Methoden im Rahmen von Spurdatenstudien in der Radikalisierungsforschung gewählt werden, illustriert exemplarisch einige Ergebnisse dieser Studien und (ii) analysiert welche Gemeinsamkeiten und Unterschiede zu traditionellen Studien wie Fragebogen- oder Experimentalstudien bestehen. Grundlage für den Überblick liefern 63 Studien, von denen allerdings nur eine geringe Anzahl (k = 18) digitale Verhaltensspurdaten nutzten, während der Großteil aus traditionellen Zugängen (k = 52) besteht. Die Ergebnisse zeigen, dass Spurdatenstudien größtenteils darauf abzielten, Personen mit radikalen Einstellungen zu identifizieren und die Entwicklung radikaler Ansichten vorherzusagen. Insgesamt eröffnen sich durch Verhaltensspurdaten bisher ungenutzte Potentiale für die Analyse von Persönlichkeitsprofilen und die Untersuchung dynamischer sozialer Interaktionen derjenigen, die anfällig für extremistische Rekrutierung sind.Eine englische Übersetzung als Rohfassung dieses Artikels finden Sie als Elektronisches Supplement 1.


Big Data in Radicalization Research. A Systematic Review

Abstract. Research into extremist radicalisation has been given a new momentum by digital traces of behaviour, such as social media posts or publicly accessible media. Against the background that Big Data is seen as an ‚epistemological revolution‘, this systematic literature review provides an overview of (i) the goals, data sources, and methods of trace data analysis chosen in radicalization research, as well as exemplifies some of the results of these studies, and (ii) analyzes the similarities and differences with traditional studies such as questionnaires or experimental studies. This overview is based on 63 studies, of which, however, only a small proportion (k = 18) used digital behavioural trace data, while the majority consist of traditional approaches (k = 52). The results show that trace data studies were largely aimed at identifying individuals with radical attitudes and predicting the development of radical views. Overall, behavioural trace data open up previously untapped potential for the analysis of personality profiles and the investigation of dynamic social interactions of those susceptible to extremist recruitment.

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