Comparing the Online Posting Behaviors of Violent and Non-Violent Right-Wing Extremists
Despite the ongoing need for researchers, practitioners, and policymakers to identify and assess the online activities of violent extremists prior to their engagement in violence offline, little is empirically known about their online behaviors generally or differences in their posting behaviors com...
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| Beteiligte: | ; ; ; |
| Medienart: | Elektronisch Aufsatz |
| Sprache: | Englisch |
| Veröffentlicht: |
2023
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| In: |
Terrorism and political violence
Jahr: 2023, Band: 35, Heft: 1, Seiten: 192-209 |
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Volltext (lizenzpflichtig) |
| Journals Online & Print: | Lade...
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| Verfügbarkeit prüfen: | HBZ Gateway |
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| Zusammenfassung: | Despite the ongoing need for researchers, practitioners, and policymakers to identify and assess the online activities of violent extremists prior to their engagement in violence offline, little is empirically known about their online behaviors generally or differences in their posting behaviors compared to non-violent extremists who share similar ideological beliefs particularly. In this study, we drew from a unique sample of violent and non-violent right-wing extremists to compare their posting behaviors within a sub-forum of the largest white supremacy web-forum. Analyses for the current study proceeded in three phases. First, we plotted the average posting trajectory for users in the sample, followed by an assessment of the rates at which they stayed active or went dormant in the sub-forum. We then used logistic regression to examine whether specific posting behaviors were characteristic of users’ violence status. The results highlight a number of noteworthy differences in the posting behaviors of violent and non-violent right-wing extremists, many of which may inform future risk factor frameworks used by law enforcement and intelligence agencies to identify credible threats online. We conclude with a discussion of the implications of this analysis, its limitations and avenues for future research. |
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| ISSN: | 1556-1836 |
| DOI: | 10.1080/09546553.2021.1891893 |