Women in ISIS Propaganda: A Natural Language Processing Analysis of Topics and Emotions in a Comparison with Mainstream Religious Group

TL;DR

This study uses NLP techniques to analyze ISIS propaganda targeting women, comparing it with mainstream religious group content to understand emotional appeals and thematic differences for counterterrorism insights.

Contribution

It introduces a comparative NLP analysis of ISIS and mainstream religious group propaganda, focusing on topics and emotions to inform counterterrorism strategies.

Findings

ISIS and Catholic materials evoke similar emotions

Propaganda themes differ between ISIS and religious groups

NLP methods reveal emotional and topical similarities

Abstract

Online propaganda is central to the recruitment strategies of extremist groups and in recent years these efforts have increasingly extended to women. To investigate ISIS' approach to targeting women in their online propaganda and uncover implications for counterterrorism, we rely on text mining and natural language processing (NLP). Specifically, we extract articles published in Dabiq and Rumiyah (ISIS's online English language publications) to identify prominent topics. To identify similarities or differences between these texts and those produced by non-violent religious groups, we extend the analysis to articles from a Catholic forum dedicated to women. We also perform an emotional analysis of both of these resources to better understand the emotional components of propaganda. We rely on Depechemood (a lexical-base emotion analysis method) to detect emotions most likely to be evoked in readers of these materials. The findings indicate that the emotional appeal of ISIS and Catholic materials are similar