J.M. Berger

THE LAST TWITTER CENSUS

The newest VOX-Pol Publication, The Last Twitter Census by JM Berger, is now available on the VOX-Pol website.

This open-access report compares two large random samples of Twitter accounts that tweet in English: one taken just before Elon Musk acquired Twitter in October 2022, and one taken three months later, in January 2023. It also examines several related datasets collected during the period following the acquisition, a period in which, the study found, new accounts were created at a record-breaking pace.


LAWFUL EXTREMISM

Academics usually define extremism as a set of beliefs that fall outside the norms of the society in which they are situated, but entire societies have at times been organized around recognizably extreme beliefs. This paper will examine the U.S. Supreme Court decision in Scott v. Sandford, 60 US 393 (1856), aka the Dred Scott decision, which ruled that Black people, whether enslaved or free, were entitled to no rights under the Constitution.

The paper analyzes the Dred Scott decision to consider whether and how it implements and institutionalizes many widely recognized tropes of extremist ideology. The paper will conclude with a discussion of empirical frameworks that can enable and empower the study of lawful extremism.


THE INTELWIRE WEEKLY BRIEF

J.M. Berger's weekly newsletter on extremism, including the latest research, current trends, historically relevant data, and bad things happening on the Internet. Formerly titled "World Gone Wrong." You can get the newsletter by e-mail or through LinkedIn, where a permanent link can also be found. 

About J.M. Berger

J.M. Berger is a writer and researcher focused on extremism as a Senior Research Fellow for the Center on Terrorism, Extremism, and Counterterrorism at the Middlebury Institute of International Studies. His research encompasses extremist and terrorist ideologies and propaganda, including social media and semantic analytical techniques. He is the author of four books, including Extremism (2018) and Optimal (2020). 

Berger's most recent nonfiction book, Extremism (MIT Press, August 2018), was named an Outstanding Academic Title for 2019 and has been reviewed as "meticulous," "an excellent primer," "exceptional" and "elegantly written." 

His debut novel, Optimal (2020), is a dystopian tale about a world run by algorithms and social media. Reviewers have praised it as "gripping," "absorbing" and "great storytelling." A member of the Science Fiction and Fantasy Writers Association, Berger is currently working on his second novel, a fantasy epic grounded in his research on extremism

Berger is also a research fellow with VOX-Pol and a PhD candidate at Swansea University's School of Law, where he studies extremist ideologies. As a consultant for social media companies and government agencies, Berger conducts research and training on issues and policies related to homegrown terrorism, online extremism, advanced social media analysis, and countering violent extremism (CVE). He is a member of the advisory board of the RESOLVE Network and a contributing writer to The Atlantic.  

A PALER SHADE OF WHITE 

Discussions of extremist ideologies naturally focus on how in-groups criticize and attack out-groups. But many important extremist ideological texts are disproportionately focused on criticizing their own in-group. A new research report from J.M. Berger uses linkage-based analysis to examine Siege, a White nationalist tract that has played an important role in shaping modern neo-Nazi movements, including such violent organizations as Atomwaffen Division and The Base. While Siege strongly attacks out-groups, including Jewish and Black people, the book is overwhelmingly a critique of how the White people of its in-group fall short of Nazi ideals. Siege’s central proposition—that the White in-group is disappointing, deeply corrupt, and complacent—shapes its argument for an “accelerationist” strategy to hasten the collapse of society in order to build something entirely new. 

Read the RESOLVE Network report 

Related on GNET: The Out-Group in the In-Group