Affiliation:
1. The University of Texas at Austin, USA
Abstract
What does antisemitism look like in the context of political discussions on Twitter? In this article, we introduce the notion of platformed antisemitism. We first define it as a platform-agnostic concept, and then explore it through an exemplary case study of Twitter and its affordances by way of a mixed-methods analysis of discourse surrounding the 2018 US midterm election. Via qualitative textual analysis, we document how political discourse on Twitter is marred by antisemitic conspiracy theories that intersect with QAnon and Trump/MAGA support. Through quantitative content analysis of a sample of 99,062 tweets, we highlight a list of terms and hashtags most often associated with antisemitic speech on Twitter and showcase how specific affordances on the platform (quote-tweets, hashtags) amplify and/or diminutize antisemitic speech. Via Lasso regression, we introduce an antisemitism classifier that can be used to further refine future detection efforts of antisemitic speech.
Subject
Sociology and Political Science,Communication
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