Hate Speech and Hate Crime: A Cross-Disciplinary Analysis of Xenophobia in Greece

Abstract

This paper investigates the correlation of hate speech and hate crime, in a inter-disciplinary approach, using a computational hate speech and hate crime detection method in a socio-political science framework, coupling Natural Language Processing with Political Sciences. The study focuses on Greece in the turbulent period from 2015 to 2022 (a period marked by economic, refugee, foreign policy, and pandemic crises); it analyzes tweets to discern linguistic patterns used to verbally attack predefined target groups consisting of ethnic and religious minorities in the country. Furthermore, it investigates hate crimes reported in the press, against the same target groups and during the same period and proceeds to examine correlations between xenophobic attitudes expressed verbally through social media, and those manifested as physical attacks in real life.

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