The normalisation of hate speech, including antisemitic rhetoric, poses a significant threat to social cohesion and democracy. While global efforts have been made to counter contemporary antisemitism, there is an urgent need to understand its online manifestations. Hate speech spreads easily across the internet, facilitated by anonymity and reinforced by algorithms that favour engaging--even if offensive--content. It often takes coded forms, making detection challenging. Antisemitism in Online Communication addresses these issues by analysing explicit and implicit antisemitic statements in mainstream online discourse. Drawing from disciplines such as corpus linguistics, computational linguistics, semiotics, history, and philosophy, this edited collection examines over 100,000 user comments from three language communities. Contributors explore various facets of online antisemitism, including its intersectionality with misogyny and its dissemination through memes and social networks. Through case studies, they examine the reproduction, support, and rejection of antisemitic tropes, alongside quantitative assessments of comment structures in online discussions. Additionally, the volume delves into the capabilities of content moderation tools and deep-learning models for automated hate speech detection. This multidisciplinary approach provides a comprehensive understanding of contemporary antisemitism in digital spaces, recognising the importance of addressing its insidious spread from multiple angles.

This book is included in DOAB.