Journal Article |
Testing a probabilistic model of desistance from online posting in a right-wing extremist forum: distinguishing between violent and non-violent users
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Little is known about online behaviours of violent extremists generally or differences compared to non-violent extremists who share ideological beliefs. Even less is known about desistance from posting behaviour. A sample of 99 violent and non-violent right-wing extremists to compare their online patterns of desistance within a sub-forum of the largest white supremacy web-forum was analysed. A probabilistic model of desistance was tested to determine the validity of criteria set for users reaching posting desistance. Findings indicated that the criteria predicted “true” desistance, with 5% misidentification. Each consecutive month without posting in the sub-forum resulted in a 7.6% increase in odds of posting desistance. There were no significant differences in effects for violent versus non-violent users, though statistical power was low.
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2024 |
Wojciechowski, T.W., Scrivens, R., Freilich, J.D., Chermak, S.M. and Frank, R. |
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Journal Article |
Comparing the Online Posting Behaviors of Violent and Non-Violent Right-Wing Extremists
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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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2021 |
Scrivens, R., Wojciechowski, T.W., Freilich, J.D., Chermak, S.M. and Frank, R. |
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VOX-Pol Blog |
Comparing the Online Posting Behaviors of Violent and Non-Violent Right-Wing Extremists
View Abstract
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2021 |
Scrivens, R., Wojciechowski, T. W., Freilich, J. S., Chermak, S. M., and Frank. R. |
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Publisher
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VOX-Pol Blog |
Differentiating Online Posting Behaviors of Violent and Nonviolent Right-Wing Extremists
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2022 |
Scrivens, R., Wojciechowski, T. W., Freilich, J. D., Chermak, S. M. and Frank, R. |
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Publisher
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Journal Article |
Examining Online Indicators of Extremism in Violent Right-Wing Extremist Forums
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Although many law enforcement and intelligence agencies are concerned about online communities known to facilitate violent right-wing extremism, little is empirically known about the presence of extremist ideologies, expressed grievances, or violent mobilization efforts that make up these spaces. In this study, we conducted a content analysis of a sample of postings from two of the most conspicuous right-wing extremist forums known for facilitating violent extremism, Iron March and Fascist Forge. We identified a number of noteworthy posting patterns within and across forums that may assist law enforcement and intelligence agencies in identifying credible threats online.
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2021 |
Scrivens, R., Osuna, A.I., Chermak, S.M., Whitney, M.A. and Frank, R. |
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Publisher
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VOX-Pol Blog |
Examining Online Indicators of Extremism in Violent Right-Wing Extremist Forums
View Abstract
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2021 |
Scrivens, R., Osuna, A. I., Chermak, S. M., Whitney, M., and Frank, R. |
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