From 2020 to 2024 the international interdisciplinary research project “Decoding Antisemitism: An AI-driven Study on Hate Speech and Imagery Online” was carried out by a research team at the Center for Research on Antisemitism, Technical University Berlin in collaboration with the University of Applied Sciences (HTW) Berlin, the University of Michigan’s School of Information, Cardiff’s HateLab and King’s College London. The research project examined antisemitism on social media at both content and linguistic-visual levels. The project researchers developed a guide that defines the diversity of antisemitic concepts and compares their linguistic and visual patterns. The guide makes it possible to identify and analyze antisemitic content in large datasets according to a fixed framework. In parallel, antisemitic hate speech online was documented. Experts in the project searched the most important forums of online political debate: social media platforms and mainstream media websites. The focus was on discourses in the United Kingdom, Germany, and France. The project’s multi-stage methodological design aimed to capture the complexity and diversity of antisemitism as well as related trends on the internet. The project team produced a variety of publications accessible online.[1]
The key findings and analyses of the innovative research project are presented in the volume under review here, published in 2024. The different chapters cover case studies, antisemitism in conservative web milieus, “Pop” antisemitism and deviant communities, the use of the concept of genocide in UK online debates about Israel, countering antisemitism online, multimodal cognitive anchoring in antisemitic memes, new approaches to detect antisemitism online which often takes subtle or implicit forms and is therefore more difficult to identify and finally the problem of algorithms and the automated detection of antisemitism which has been little explored compared to other forms of hate speech. The authors point out the problem of wordplay and the combination of letters and imagery that are recognized within the scene but are unfamiliar to the general public. For example, the American-Jewish philanthropist and hedge fund manager George Soros, who has become a figurehead for conspiracy theorists and has in many places taken on the role of the Rothschild family—which carries antisemitic connotations—is depicted on social media with a small snake emoji standing for “s,” the letters “oro,” and, finally, the emoji snake again. The snake icons imply malice and deceit—classic antisemitic motifs. Many social media posts use implicit language through allusions, in which a word or phrase is used but placed in a new, seemingly incompatible context. For example, terms posted online such as “Final Solution to the Palestinian Question,” “Fourth Reich,” “Hamas = Resistance 2.0,” and “Gaza = Warsaw” illustrate how Holocaust distortion spreads on the internet. Indirect speech acts—such as rhetorical questions, irony, sarcasm, and jokes—pose a particular challenge, as they are often accompanied by content with antisemitic undertones, in which terms like greed, money, wealth in connection with Jews as well as oppression, and ethnic cleansing in connection with Israel are used.
The interactive web has generated a huge amount of data. Due to the large presence of hateful content, different new techniques have been developed to track antisemitism and other forms of hate speech. Yet qualitative approaches to antisemitic web comments have so far attracted little attention. And it is qualitative analysis, even more than quantitative work, that provides the basis for countering antisemitism online. The view that counter-speech is helpful to react against antisemitic content on the web is still very widespread. However, it has become clear that this actually contributes to the further spread of such content and is therefore not really the right approach to countering and combating antisemitism online.
Drawing on various significant events that triggered antisemitic content online—such as the escalation of the Middle East conflict, the war in Ukraine, Kanye West’s antisemitic remarks, the Labour Party and Jeremy Corbyn’s antisemitism, and the debates around “documenta 15”—the book shows how public debate fuels antisemitic rhetoric and pushes the boundaries of what is acceptable to say in public ever further.
The publication provides valuable insight into the dissemination of antisemitic content in the form of text, words, and imagery—such as memes—on social media. Throughout the individual chapters, there are frequent references to another publication by the research team, which provides a comprehensive guide to explicit and coded forms of contemporary antisemitism: “Decoding Antisemitism: A Guide to Identifying Antisemitism Online.”[2]
[1] https://decoding-antisemitism.eu/publications (accessed July 4, 2026).
[2] https://link.springer.com/content/pdf/10.1007/978-3-031-49238-9.pdf (accessed July 4, 2026).
