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Bo Min Keum
Areas of interest
Online subcultures and radicalization; violent extremism; disengagement and intervention program evaluation; machine-learning applications in Preventing and Countering Violent Extremism (P/CVE)
Biography
Bo Min Keum is a PhD student in the International CyberCrime Research Centre and School of Criminology at SFU. She completed her B.A. Honours (with Distinction) in Criminology at SFU and her MPhil in Criminological Research at the University of Cambridge. Her previous work focused on pathways into violent extremism. Now, she studies where extremism can lead: learned helplessness, nihilism, disengagement, or something else. She is particularly interested in the memetic and performative aspects of extremism, practices uniquely afforded in online spaces that provide affective and/or symbolic gratification. And paradoxically, eventual disillusionment.
Her work combines qualitative, quantitative, and historical archival research. To name a few: a Campbell Systematic Review of violent extremism disengagement programs; historical archival research of online subcultures from the 1990s to the 2010s; and interviews with former extremists. Overall, her research is about asking why, even under the same Internet affordances, pathways diverge toward and against violence.
She welcomes conversations with anyone interested in discussing these questions further.
Projects
Interventions to Prevent Cognitive and Behavioural Violent Radicalization: A Systematic Review and Multi-Level Meta-Analysis
A Campbell Systematic Review of 19 extremism interventions (spanning 2013-2024) aimed at preventing radicalization, with 118 effect sizes and representing 8,910 participants. Under peer-review by the Campbell Collaboration.
The Dark Crawler: Combating Disinformation Warfare with Artificial Intelligence
Funded by the Defence Sciences Division of Public Works and Government Services Canada, this project involved analyzing disinformation campaigns to establish the 'ground truth' for discerning between real information and disinformation. 2,500 tweets were coded into thematic patterns, which were used to assess the classification accuracy of machine-learning algorithms.
Publications
The Incel Paradox: Hating Others, While Hating Themselves?
How Does Incel Research Look to a Former Incel?