A Department of Homeland Security Emeritus Center of Excellence led by the University of Maryland

A consortium of researchers dedicated to improving the understanding of the human causes and consequences of terrorism

Psychology and Morality of Political Extremists: Evidence from Twitter Language Analysis of Alt-right and Antifa


Psychology and Morality of Political Extremists: Evidence from Twitter Language Analysis of Alt-right and Antifa

Abstract: 

The recent rise of the political extremism in Western countries has spurred renewed interest in the psychological and moral appeal of political extremism. Empirical support for the psychological explanation using surveys has been limited by lack of access to extremist groups, while field studies have missed psychological measures and failed to compare extremists with contrast groups. We revisit the debate over the psychological and moral appeal of extremism in the U.S. context by analyzing Twitter data of 10,000 political extremists and comparing their text-based psychological constructs with those of 5000 liberal and 5000 conservative users. The results reveal that extremists show a lower positive emotion and a higher negative emotion than partisan users, but their differences in certainty is not significant. In addition, while left-wing extremists express more language indicative of anxiety than liberals, right-wing extremists express lower anxiety than conservatives. Moreover, our results mostly lend support to Moral Foundations Theory for partisan users and extend it to the political extremists. With the exception of ingroup loyalty, we found evidences supporting the Moral Foundations Theory among left- and right-wing extremists. However, we found no evidence for elevated moral foundations among political extremists.

Publication Information

Full Citation: 

Alizadeh, Meysam, Ingmar Weber, Claudio Cioffi-Revilla, Santo Fortunato, and Michael Macy. 2019. "Psychology and Morality of Political Extremists: Evidence from Twitter Language Analysis of Alt-right and Antifa." EPJ Data Science 8 (May). https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-019-0193-9

START Author(s): 
Claudio Cioffi-Revilla
Publication URL: 
Visit Website