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

by   Mojtaba Heidarysafa, et al.

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


page 1

page 2

page 3

page 4


Natural Language Processing for Cognitive Analysis of Emotions

Emotion analysis in texts suffers from two major limitations: annotated ...

NLP meets psychotherapy: Using predicted client emotions and self-reported client emotions to measure emotional coherence

Emotions are experienced and expressed through various response systems....

Emotional Embeddings: Refining Word Embeddings to Capture Emotional Content of Words

Word embeddings are one of the most useful tools in any modern natural l...

The emotional arcs of stories are dominated by six basic shapes

Advances in computing power, natural language processing, and digitizati...

Measuring the Diversity of Facebook Reactions to Research

Online and in the real world, communities are bonded together by emotion...

Please sign up or login with your details

Forgot password? Click here to reset