A Quantitative Approach to Understanding Online Antisemitism

Abstract

A new wave of growing antisemitism, driven by fringe Web communities, is an increasingly worrying presence in the socio-political realm. The ubiquitous and global nature of the Web has provided tools used by these groups to spread their ideology to the rest of the Internet. Although the study of antisemitism and hate is not new, the scale and rate of change of online data has impacted the efficacy of traditional approaches to measure and understand these troubling trends.In this paper, we present a large-scale, quantitative study of online antisemitism. We collect hundreds of million posts and images from alt-right Web communities like 4chan's Politically Incorrect board (/pol/) and Gab. Using scientifically grounded methods, we quantify the escalation and spread of antisemitic memes and rhetoric across the Web. We find the frequency of antisemitic content greatly increases (in some cases more than doubling) after major political events such as the 2016 US Presidential Election and the “Unite the Right” rally in Charlottesville. We extract semantic embeddings from our corpus of posts and demonstrate how automated techniques can discover and categorize the use of antisemitic terminology. We additionally examine the prevalence and spread of the antisemitic “Happy Merchant” meme, and in particular how these fringe communities influence its propagation to more mainstream communities like Twitter and Reddit. Taken together, our results provide a data-driven, quantitative framework for understanding online antisemitism. Our methods serve as a framework to augment current qualitative efforts by anti-hate groups, providing new insights into the growth and spread of hate online.

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Contextual-Aware and Expert Resources for Brazilian Portuguese Hate Speech Detection

“…1. Antisemitism: The definition of antisemitism adopted by the IHRA 5 in 2016 states that "Antisemitism is a certain perception of Jews, which may be expressed as hatred towards Jews. Rhetorical and physical manifestations of antisemitism might include the targeting of the state of Israel, conceived as a Jewish collectivity", as in the example "Que escroto caquético!…”

“…We must point out that a couple of comments belongs to more than a group. For example, the comment comunista vagabunda e safada ("shameless communist slut") was classified as partyism and sexism, hence it was labeled as (5,8). Offensive comments without hate speech were labeled as (-1).…”

“…Hate speech and offensive language detection tasks have attracted interest from different institutions and have become an important research topic [3][4][5][6][7][8][9][10]. Moreover, although this kind of investigation is undoubtedly a relevant topic, the proposition of automated methods also has its implications for unprejudiced societies concerning race, gender, religion, origin, etc.…”

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