Abstract: Over the past 3.5 years, the Decoding Antisemitism research project has been analysing antisemitism on the internet in terms of content, structure, and frequency. Over this time, there has been no shortage of flashpoints which have generated antisemitic responses. Yet the online response to the Hamas attacks of 7 October and the subsequent Israeli operations in Gaza has surpassed anything the project has witnessed before. In no preceding escalation phase of the Arab-Israeli conflict has the predominant antisemitic reaction been one of open jubilation and joy over the deaths of Israeli Jews. As demonstrated in the sixth and final Discourse Report, this explicit approval of the Hamas attacks was the primary response from web users. The response to 7 October therefore represents a turning point in antisemitic online discourse, and its repercussions will be felt long into the future.
The report contains analysis of the various stages of online reactions to events in the Middle East, from the immediate aftermath to the Israeli retaliations and subsequent accusations of genocide against Israel. As well as examining online reactions in the project’s core focus—the United Kingdom, France, and Germany—this report also, for the first time, extends its view to analyse Israel-related web discourses in six further countries, including those in Southern and Eastern Europe as well as in North Africa. Alongside reactions to the escalation phase, the report also examines online responses to billionaire Elon Musk’s explosive comments about Jewish individuals and institutions.
Additionally, the report provides a retrospective overview of the project’s development over the past 3.5 years, tracking its successes and challenges, particularly regarding the conditions for successful interdisciplinary work and the ability of machine learning to capture the versatility and complexity of authentic web communication.
To mark the publication of the report, we are also sharing our new, interactive data visualisations tool, which lets you examine any two discourse events analysed by our research team between 2021 and 2023. You can compare the frequencies and co-occurrences of antisemitic concepts and speech acts by type and by country, look at frequencies of keywords in antisemitic comments, and plot keyword networks.
Topics: Antisemitism, Antisemitism: Discourse, Antisemitism: Monitoring, Internet, Social Media, Main Topic: Antisemitism, War, Terrorism, Attitudes to Israel, Israeli-Palestinian Conflict, Boycott Divestment and Sanctions (BDS)
Abstract: This article introduces the pilot project “Decoding Antisemitism: An AI-driven Study on Hate Speech and Imagery Online.” The aim of the project is to analyse the frequency, content and linguistic structure of online antisemitism, with the eventual aim of developing AI machine learning that is capable of recognizing explicit and implicit forms of antisemitic hate speech. The initial focus is on comments found on the websites and social media platforms of major media outlets in the United Kingdom, Germany, and France. The article outlines the project’s multi-step methodological design, which seeks to capture the complexity, diversity and continual development of antisemitism online. The first step is qualitative content analysis. Rather than relying on surveys, here a pre-existing “real-world” data set-namely, threads of online comments responding to media stories judged to be potential triggers for antisemitic speech-is collected and analysed for antisemitic content and linguistic structure by expert coders. The second step is supervised machine learning. Here, models are trained to mimic the decisions of human coders and learn how antisemitic stereotypes are currently reproduced in different web milieus-including implicit forms. The third step is large-scale quantitative analyses in which frequencies and combinations of words and phrases are measured, allowing the exploration of trends from millions of pieces of data.
Abstract: The 3-year pilot project presented here aims at analyzing antisemitic hate speech and imagery on mainstream news websites and social media platforms in different European contexts. Current forms of antisemitism will be examined in various ways by three international research teams from Germany, France, and the UK.
First, the datasets will be studied in detail (qualitative analysis based on pragmalinguistic, image analytical and historical approaches), taking into account explicit as well as implicit forms of communication (TU Berlin).
The resulting annotated datasets will provide training, validation, and test data for supervised machine learning techniques (King’s College London).
Eventually, all studied phenomena will be measured over time through statistical/quantitative analysis (TU Berlin and King’s College London).
The project stands in contrast to previous quantitative research on antisemitism online due to a) its awareness of verbal and visual complexity in the respective cultural and situational contexts, and b) its detailed, multimodal approach. Thus, it will provide the most accurate picture yet of the full extent of Jew-hatred on the interactive web.
The focus of the pilot project will be on German, English and French websites and their respective social media platforms. After the initial three year period, the focus will broaden out to investigate other European language communities.
The project will make a major contribution to the study of viral hate in different cultural contexts. Moreover, the researchers will engage in an ongoing dialogue not only with academia, but also with political, media and pedagogical institutions. An additional output will be an open source tool that will help to identify the full extent of antisemitism in various web milieus.
The half-yearly discourse reports share central insights of the ongoing research outcomes of the project "Decoding Antisemitism" and review unfolding trends.
The second discourse report presents the definitional basis of our analyses and for the first time provides comprehensive insights into our corpus analyses relating to Great Britain, France and Germany.
Abstract: The 3-year pilot project presented here aims at analyzing antisemitic hate speech and imagery on mainstream news websites and social media platforms in different European contexts. Current forms of antisemitism will be examined in various ways by three international research teams from Germany, France, and the UK.
First, the datasets will be studied in detail (qualitative analysis based on pragmalinguistic, image analytical and historical approaches), taking into account explicit as well as implicit forms of communication (TU Berlin).
The resulting annotated datasets will provide training, validation, and test data for supervised machine learning techniques (King’s College London).
Eventually, all studied phenomena will be measured over time through statistical/quantitative analysis (TU Berlin and King’s College London).
The project stands in contrast to previous quantitative research on antisemitism online due to a) its awareness of verbal and visual complexity in the respective cultural and situational contexts, and b) its detailed, multimodal approach. Thus, it will provide the most accurate picture yet of the full extent of Jew-hatred on the interactive web.
The focus of the pilot project will be on German, English and French websites and their respective social media platforms. After the initial three year period, the focus will broaden out to investigate other European language communities.
The project will make a major contribution to the study of viral hate in different cultural contexts. Moreover, the researchers will engage in an ongoing dialogue not only with academia, but also with political, media and pedagogical institutions. An additional output will be an open source tool that will help to identify the full extent of antisemitism in various web milieus.
The half-yearly discourse reports share central insights of the ongoing research outcomes of the project "Decoding Antisemitism" and review unfolding trends.
The first discourse report provides insight into the methodological approaches and the nature of antisemitic hate speech in selected discourse spaces.
