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This study explores the utility of a sociological model of social organization developed by Best and Luckenbill (1994) to classify the radicalization processes of terrorists (i.e., extremist perpetrators who engaged in ideologically motivated acts of violence) who are usually categorized as loner or lone wolf attackers. There are several organizational frameworks used to define or classify violent acts performed by individuals who may or may not have ties to extremist groups, but these studies largely ignore the role of social relationships in radicalization and the extent to which they inform our knowledge of terror. To address this gap, we apply the Best and Luckenbill model of social organization using a qualitative analysis of three case studies of four lone actor or small cell terrorists. The findings demonstrate lone actors are not always true loners in the context of radicalization, and highlights the ways that the Internet and social ties foster the radicalization processes of terror.

This document reports findings from a Rapid Evidence Assessment conducted on the role of mass and social media during and after terrorist events. It is designed to bring together and synthesize insights and evidence from the available published research literature to inform future policy and practice development. By promoting understanding of how different forms of mediated communication shape what happens in the aftermath of terror events, the work seeks to reflect changes in both the conduct of terrorism and the contemporary information environment. In particular, the spread of social media has had disruptive and transformative impacts upon press and broadcast journalism, and the ways
that terrorist violence is performed.

VOX-Pol Guest Lecture Series, Spring 2024: Data Collection in Online Terrorism and Extremism Research

There has been a growing interest among researchers, practitioners, and policymakers to analyze the online activities of extremists and terrorists. As studies in this research area have increased, various data collection techniques have emerged to address key research questions, ranging from manual extraction to computational tools to collect online information. This lecture examines the strengths and limitations of commonly used data collection methods in online terrorism and extremism research. We draw from our research experiences and highlight ethical dilemmas with collection methods in practice. We then set forth suggestions for progressing research in this space. For more information on data collection in online terrorism and extremism research, see our recent article in Studies in Conflict & Terrorism as part of a special issue on the strengths and struggles of different methods of research on radicalization, extremism, and terrorism: https://www.tandfonline.com/doi/full/10.1080/1057610X.2024.2361957?src=exp-la

Ryan Scrivens is an Assistant Professor in the School of Criminal Justice at Michigan State University. He is also an Associate Director at the International CyberCrime Research Centre at Simon Fraser University and a Research Fellow at the VOX-Pol Network of Excellence. He is the recipient of the 2022 Early Career Impact Award from the American Society of Criminology’s Division on Terrorism and Bias Crimes.

Steven Chermak is a Professor in the School of Criminal Justice at Michigan State University. He is the co-creator of several databases including the Extremist Crime Database (ECDB), the Extremist Cybercrime Database (ECCD), and The American School Shooting Study (TASSS). He is the recipient of the 2021 Distinguished Scholar Award from the American Society of Criminology’s Division on Terrorism and Bias Crimes.

VOX-Pol Blog post.

The theoretical literature from criminology, social movements, and political sociology, among others, includes diverging views about how political outcomes could affect movements. Many theories argue that political defeats motivate the losing side to increase their mobilization while other established models claim the winning side may feel encouraged and thus increase their mobilization. We examine these diverging perspectives in the context of the extreme right online and recent presidential elections by measuring the effect of the 2008 and 2016 election victories of Obama and Trump on the volume of postings on the largest white supremacy web-forum. ARIMA time series using intervention modeling showed a significant and sizable increase in the total number of posts and right-wing extremist posts but no significant change for firearm posts in either election year. However, the volume of postings for all impact measures was highest for the 2008 election.

VOX-Pol Blog post.