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About the Project

This project studies coded antisemitic hate speech and trope evolution with the goal of developing machine-learning detection and monitoring tools. With the ubiquity of the internet and social media, technology has increased the speed at which language evolves. Propaganda in the form of hate speech now travels the world at such a dizzying pace that it is beyond the ability of social media platforms or governments to effectively monitor and control. Harmful words unfold, take on new meanings in both direct and coded ways, quickly inciting hatred in the minds of those only too willing to believe them because they reinforce and justify preexisting prejudicial views.

 

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Organization of the Research

Three Teams

Textual Analysis (Wendy Meilillo)
-Expertise: Text Analysis, Coded Language

Population Analysis (Jeff Gill)
-Expertise: Survey Methods, Political Analysis

Software Design (Nathalie Japkowicz)
-Expertise: AI, Natural Language Processing, Machine Learning

Research

Research Goals

Discover and Monitor
-Emergent Antisemitic Coded Language

Identify
-New (or New Variations of) Antisemitic Tropes

Determine
-The Flow of coded terminology from extremist communities to the general public

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A Cohesive Multi-Disciplinary Approach

  • Textual analysis to search for hidden terminology used in extremist communities to express antisemitism. Detection of new antisemitic tropes. 
  • Survey analysis to identify the content that flows from the extremist minority to the general public.
  • Automatic monitoring of the evoluation of antisemitic terminology and discourse. NLP and Deep Learning Tools to simply data collection and textual analysis.
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