Detecting markers of radicalisation in social media posts : the role of person-centric and psychosocial risk factors, and protective factors

The ubiquity of online radicalisation warrants the need for law enforcement to learn how to harness open-source intelligence to assess the threat posed and identify potential terrorists in advance. Although much is known about the online radicalisation process, there is a lack of risk assessment ins...

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Bibliographic Details
Main Author: Neo, Loo Seng
Other Authors: Ring Joyce Pang Shu Min
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/145173
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Institution: Nanyang Technological University
Language: English
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Summary:The ubiquity of online radicalisation warrants the need for law enforcement to learn how to harness open-source intelligence to assess the threat posed and identify potential terrorists in advance. Although much is known about the online radicalisation process, there is a lack of risk assessment instruments developed specifically for online radicalisation, as well as little empirical research in this field. To address these research gaps, this thesis aims to articulate a set of person-centric and psychosocial risk factors and protective factors for identifying radicalisation in social media posts. Five studies were conducted. The first study (chapter 3) involved the use of a modified Delphi technique and literature review to derive a list of 12 factors and 42 indicators. The second study (chapter 4) served as a pilot to map the said factors and indicators to two groups of supporters of terrorists who have been influenced by radical online propaganda. These two groups comprise individuals who travelled to join the Islamic State in Iraq and Syria [ISIS] (i.e., foreign fighters), and individuals who did not travel to join ISIS (i.e., sympathisers). Next, the third study (chapter 5) built upon study 2 and incorporated changes to the research design (e.g., use of multidimensional scaling, logistic regression) to map the factors and indicators to a larger sample of ISIS foreign fighters and sympathisers. The fourth study (chapter 6) was designed to replicate the research methodology of study 3 using a different sample (i.e., Kurdish fighters) to compare against ISIS fighters. Finally, the fifth study (chapter 7) detailed a survey conducted with members of the community (NTU undergraduates and MTurk workers) on their perceptions towards the indicators and their general understanding of online radicalisation and terrorism. The practical, methodological, and theoretical implications of this research as well as suggestions for future studies are discussed in chapter 8.