Using online data in terrorism research
Stuart Macdonald,
Elizabeth Pearson,
Ryan Scrivens and
Joe Whittaker
Chapter 10 in A Research Agenda for Terrorism Studies, 2023, pp 145-158 from Edward Elgar Publishing
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: Law - Academic; Politics and Public Policy Sociology and Social Policy (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.elgaronline.com/view/edcoll/9781789909104/9781789909104.00016.xml (application/pdf)
Our link check indicates that this URL is bad, the error code is: 503 Service Temporarily Unavailable
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:elg:eechap:19368_10
Ordering information: This item can be ordered from
http://www.e-elgar.com
Access Statistics for this chapter
More chapters in Chapters from Edward Elgar Publishing
Bibliographic data for series maintained by Darrel McCalla ().