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Using online data in terrorism research

Stuart Macdonald Orcid Logo, Elizabeth Pearson Orcid Logo, RYAN SCRIVENS, Joe Whittaker Orcid Logo

A Research Agenda for Terrorism Studies, Pages: 145 - 158

Swansea University Authors: Stuart Macdonald Orcid Logo, Elizabeth Pearson Orcid Logo, RYAN SCRIVENS, Joe Whittaker Orcid Logo

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DOI (Published version): 10.4337/9781789909104.00016

Abstract

This chapter considers three types of online data available for researchers. First, it looks at machine learning and its use when considering the vast amount of data available to detect indicators of involvement in terrorism. Next, the chapter considers case studies and their use when addressing ‘ho...

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Published in: A Research Agenda for Terrorism Studies
ISBN: 9781789909098 9781789909104
Published: Edward Elgar Publishing 2023
URI: https://cronfa.swan.ac.uk/Record/cronfa62753
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Abstract: This chapter considers three types of online data available for researchers. First, it looks at machine learning and its use when considering the vast amount of data available to detect indicators of involvement in terrorism. Next, the chapter considers case studies and their use when addressing ‘how’ and ‘why’ questions. Given the difficulty of research with this population, case studies lend themselves to analysis of an individual terrorist’s behaviour. Finally, netnography (an ethnographic study of online communities) is reviewed with the argument that it has furthered our understanding of radicalisation. This area of research considers the intersection of online and offline relationships in mobilising people towards radicalisation. The chapter concludes with a review of the benefits and weaknesses of these different online research methods.
Keywords: Terrorism research; Machine learning; Case studies; Netnography; Online data; Radicalisation
College: Faculty of Humanities and Social Sciences
Start Page: 145
End Page: 158