Topics: Antisemitism, Antisemitism: Attitude Surveys, Antisemitism: Christian, Antisemitism: Definitions, Antisemitism: Discourse, Antisemitism: Education against, Antisemitism: Far right, Antisemitism: Left-Wing, Antisemitism: Monitoring, Antisemitism: Muslim, Antisemitism: New Antisemitism, Antisemitism: Online, Internet, Jewish Perceptions of Antisemitism, Attitudes to Jews, Anti-Zionism, Israel Criticism, Main Topic: Antisemitism, Methodology, Social Media
Abstract: This open access book is the first comprehensive guide to identifying antisemitism online today, in both its explicit and implicit (or coded) forms. Developed through years of on-the-ground analysis of over 100,000 authentic comments posted by social media users in the UK, France, Germany and beyond, the book introduces and explains the central historical, conceptual and linguistic-semiotic elements of 46 antisemitic concepts, stereotypes and speech acts. The guide was assembled by researchers working on the Decoding Antisemitism project at the Centre for Research on Antisemitism at Technische Universität Berlin, building on existing basic definitions of antisemitism, and drawing on expertise in various fields. Using authentic examples taken from social media over the past four years, it sets out a pioneering step-by-step approach to identifying and categorising antisemitic content, providing guidance on how to recognise a statement as antisemitic or not. This book will be an invaluable tool through which researchers, students, practitioners and social media moderators can learn to recognise contemporary antisemitism online – and the structural aspects of hate speech more generally – in all its breadth and diversity.
Abstract: The proliferation of hateful and violent speech in online media underscores the need for technological support to combat such discourse, create safer and more inclusive online environments, support content moderation and study political-discourse dynamics online. Automated detection of antisemitic content has been little explored compared to other forms of hate-speech. This chapter examines the automated detection of antisemitic speech in online and social media using a corpus of online comments sourced from various online and social media platforms. The corpus spans a three-year period and encompasses diverse discourse events that were deemed likely to provoke antisemitic reactions. We adopt two approaches. First, we explore the efficacy of Perspective API, a popular content- moderation tool that rates texts in terms of, e.g., toxicity or identity-related attacks, in scoring antisemitic content as toxic. We find that the tool rates a high proportion of antisemitic texts with very low toxicity scores, indicating a potential blind spot for such content. Additionally, Perspective API demonstrates a keyword bias towards words related to Jewish identities, which could result in texts being falsely flagged and removed from platforms. Second, we fine-tune deep learning models to detect antisemitic texts. We show that OpenAI’s GPT-3.5 can be fine-tuned to effectively detect antisemitic speech in our corpus and beyond, with F1 scores above 0.7. We discuss current achievements in this area and point out directions for future work, such as the utilisation of prompt-based models.
Abstract: Antisemitism often takes implicit forms on social media, therefore making it difficult to detect. In many cases, context is essential to recognise and understand the antisemitic meaning of an utterance (Becker et al. 2021, Becker and Troschke 2023, Jikeli et al. 2022a). Previous quantitative work on antisemitism online has focused on independent comments obtained through keyword search (e.g. Jikeli et al. 2019, Jikeli et al. 2022b), ignoring the discussions in which they occurred. Moreover, on social media, discussions are rarely linear. Web users have the possibility to comment on the original post and start a conversation or to reply to earlier web user comments. This chapter proposes to consider the structure of the comment trees constructed in the online discussion, instead of single comments individually, in an attempt to include context in the study of antisemitism online. This analysis is based on a corpus of 25,412 trees, consisting of 76,075 Facebook comments. The corpus is built from web comments reacting to posts published by mainstream news outlets in three countries: France, Germany, and the UK. The posts are organised into 16 discourse events, which have a high potential for triggering antisemitic comments. The analysis of the data help verify whether (1) antisemitic comments come together (are grouped under the same trees), (2) the structure of trees (lengths, number of branches) is significant in the emergence of antisemitism, (3) variations can be found as a function of the countries and the discourse events. This study presents an original way to look at social media data, which has potential for helping identify and moderate antisemitism online. It specifically can advance research in machine learning by allowing to look at larger segments of text, which is essential for reliable results in artificial intelligence methodology. Finally, it enriches our understanding of social interactions online in general, and hate speech online in particular.
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.
Abstract: In research on antisemitism related to Germany generally four subdimensions of hatred towards Jews are differentiate: (a) the anti-Judaism related to the Christian religion, (b) the biologically argued racial antisemitism, (c) secondary Antisemitism, and (d) antisemitism presented as antizionism. The central question in relation to the shift in how antisemitic attitudes are articulated in the German population is the dispute over whether this shift consists merely in a change in how a continuing, fundamental antisemitic attitude is articulated, and whether antisemitic attitudes have merely found another avenue of communication. The overall object of the study is to explore the structures, contexts, and dynamics of antisemitism and to focus on aspects of political psychology, hence looking at mainly collective identification, defense, and projection patterns. In terms of methodology the intention is to study the project as part of a qualitative supplementary study, based on the integration concept described by Christian Seipel and Peter Rieker of a sequence of quantitative and qualitative empirical research. The supplementary study will have as its base a sub-sample extracted from the overall results of the GMF Survey 2005. An especially suitable method for this is the Structured Depth Interview since it makes possible revealing non-communicated motives—whether consciously kept quiet or unconsciously suppressed. The main goal here is to penetrate the surface structure of antisemitism, to decipher its political-psychological dynamics, and to elaborate its associative contexts.
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: This article validates the Generalised Antisemitism (GeAs) scale, which provides a measure of antisemitism consistent with the International Holocaust Remembrance Alliance Working Definition of Antisemitism (generally known as the IHRA Definition). The GeAs scale is comprised of two 6-item subscales, each containing a balance of reverse-coded items: the Judeophobic Antisemitism (JpAs) subscale, comprised of antisemitic statements about Jews as Jews, and the Antizionist Antisemitism (AzAs) subscale, comprised of antisemitic statements about Israel and its supporters. Pre-registered tests of convergent-discriminant validity are carried out using a quota sample (n= 602), which is also used to test the pre-registered hypothesis of positive correlation between subscales. The latter is supported and shown to be robust to outliers, as well as to hold both among male and female respondents and among younger and older respondents. Test-retest reliability is measured using re-invitees from the first sample (n= 428). Data from larger samples of UK-resident adults (a quota sample balanced for age and gender, n= 809, and a representative random sample from a recruited panel, n= 1853) are used in a confirmatory factor analysis and in tests of measurement invariance. The findings provide further evidence that the GeAs scale is reliable and valid. The finding that improved fit is achieved by bifactor models featuring two group factors and a general factor is consistent with the view that statements characteristic of ‘old’ and ‘new’ antisemitism express a single underlying trait.
Abstract: Soon after the outbreak of the pandemic, antisemitism connected to the coronavirus appeared in the world. In our research we analyzed a large Hungarian online text corpus from December 1, 2019, to July 10, 2020 to examine whether coronavirus-related antisemitism was present in the Hungarian online space, and if so, what its content was. We differentiated between two layers of communication: the professionalized layer represented by online articles, and the lay one represented by comments and posts. After providing the conceptual background regarding conspiracy theories and conspiratorial- and coronavirus-related antisemitism, we present the mixed-method approach that we employed. This approach includes quantitative LDA topic models, human annotation, and the qualitative analysis of various discourses. Our research indicates that coronavirus-related antisemitism appeared in the Hungarian online space at the very beginning of the pandemic. However, at this time, until July, it was present almost solely at the lay level. Its content was mainly related to various tropes (conspiracy theories) about Jews. However, additional content was also identified. Based on our results and international examples, we propose a comprehensive typology that proved to be a suitable means of analyzing coronavirus-related antisemitic content.
Abstract: In this paper, we explore antisemitism in contemporary Hungary. After briefly introducing
the different types of antisemitism, we show the results of a quantitative survey carried out
in 2017 on a nationally representative sample. Next, we present the research we conducted
on the articles related to Jews from the far-right site Kuruc.info. Our corpus contained
2,289 articles from the period between February 28, 2016, and March 20, 2019. To identify
latent topics in the text, we employed one of the methods of Natural Language Processing
(NLP), namely topic modeling using the LDA method. We extracted fifteen topics. We found
that racial antisemitism, unmeasurable by survey research, is overtly present in the discourse of Kuruc.info. Moreover, we identified topics that were connected to other types of antisemitism.
Abstract: This article introduces a new analytical model for researching vernacular religion, which aims to capture and describe everyday religiosity as an interplay between knowing, being, and doing religion. It suggests three processes that tie this triad together: continuity; change; and context. The model is envisaged as a tool for tracing vernacular religion in ethnographic data in a multidimensional yet structured framework that is sensitive to historical data and cultural context, but also to individual narratives and nuances. It highlights the relationship between self-motivated modes of religiosity and institutional structures, as well as influences from secular sources and various traditions and worldviews.
The article is based on an ongoing research project focusing on everyday Judaism in Finland. The ethnographic examples illustrate how differently these dynamics play out in different life narratives, depending on varying emphases, experiences, and situations. By bringing together major themes recognized as relevant in previous research and offering an analytical tool for detecting them in ethnographic materials, the model has the potential to create new openings for comparative research, because it facilitates the interlinking of datasets across contexts and cultures. The article concludes that the model can be developed into a more generally applicable analytical tool for structuring and elucidating contemporary ethnographies, mirroring a world of rapid cultural and religious change.
Abstract: Was bleibt, wenn die Zeuginnen und Zeugen der nationalsozialistischen Verbrechen gestorben sein werden? Seit Jahren ist diese Frage in allen gesellschaftlichen, wissenschaftlichen und pädagogischen Debatten über den Umgang mit der NS-Geschichte präsent. Was bleibt, sind die Zeugnisse, die Überlebende in ganz unterschiedlicher Form abgelegt haben: ihre Berichte, ihre literarischen, musikalischen und bildnerischen Verarbeitungen, ihre lebensgeschichtlichen Erzählungen, ihre Zeugenaussagen vor Gericht. Sie vermitteln eindrücklich die Auswirkungen und Schrecken der nationalsozialistischen Verfolgung. Aber sind sie Garanten dafür, dass die spezifische Erfahrungsgeschichte der NS-Opfer auch künftig in der öffentlichen Erinnerungskultur und in der Bildung bewahrt werden wird? Welchen Stellenwert haben sie in der Geschichtsforschung zu Nationalsozialismus und Holocaust? Und wie lassen sie sich in der Bildungspraxis am besten einsetzen? Die Veranstaltungsreihe „Entdecken und Verstehen. Bildungsarbeit mit Zeugnissen von Opfern des Nationalsozialismus“ der Stiftung „Erinnerung, Verantwortung und Zukunft“ (EVZ) ist diesen Fragen nachgegangen. In fünf Seminaren wurden neueste Forschungsergebnisse sowie konkrete Bildungsmodule zu den wichtigsten Zeugnisformen vorgestellt und diskutiert. Die Resultate der Reihe sind in diesem Band dokumentiert
Abstract: This thesis examines the issue of ethnicity and kinship and explores the advent of identity formation, specifically in a Reform Jewish context, via youth movement participation. Through the mediums of informal education, focus group discussion and individual semi-structured interviews, I engage in an exploration of identifying what it means to be Jewish, how youth movements augment and abet Jewish identity formation, and the boundaries that exist between young Jews and their host communities.
Youth movement youngsters are observed in situ and Grounded Theory (Strauss, 1987; Glaser, 1978; Glaser, 1992; Glaser, 1998; Glaser, and Strauss, 1968) is employed to elucidate their engagements and interactions. Three case studies (Stake, 1995) are then presented to illustrate the experience of youth movement “graduates”. Interpretative Phenomenological Analysis (Smith, 2004; Smith and Osborn, 2003) is used to consider the dimensions of their relationship to Judaism, their youth movement and mainstream society.
I conclude that Jewish Identity is a combination of the Motivational and the Situational imperatives. The combined values of religion, culture and national affinity provide the motivational forces. Situational factors inducing Jewish identity amongst youth movement members are the ever wider boundaries they create for themselves and that are created for them. The first boundary of these youngsters that I identify is their movement loyalty relative to other Jewish youth movements; the next is their Reform Judaism within a wider Jewish context and the broader category is their “Jewishness” in a wider society. This “Jewishness” is expressed through the desire for Jewish Continuity (the future of the Jewish people) and the perpetuation of the feeling of “otherness”.
The final chapter charts my developing identity as a researcher. I pose and answer questions taken from throughout the thesis to illustrate my trajectory along the route of becoming a researcher and interpolating my Jewish roots and their significance in my identity development.
Abstract: In the aftermath of the spike in antisemitic incidents during the war in Gaza in summer 2014, and the Islamist attacks on Jews in Brussels, Paris and Copenhagen, there is growing concern about rising antisemitism in Europe. Yet, as this paper shows, existing data present a complex and multi-faceted picture of reality, proving some existing hypotheses beyond any reasonable doubt, but challenging others.
It is clear, for example, that spikes in antisemitic incidents occur when war breaks out in Gaza – all data sources from multiple countries and both Jewish and non-Jewish sources show this. However, it is far less clear whether or not levels of antisemitism are rising over time in the UK: different sources of data tell competing stories, and the absence of trend data on patterns of reporting among British Jews makes it difficult to draw any firm conclusions. We can see that antisemitic sentiment is particularly strong among certain sub-groups within the population, but we can also see that, taken as a whole, British adults hold largely favourable attitudes towards Jews, at levels that place Britain among the least antisemitic countries in the world.
Nevertheless, the data indicate that significant proportions of Jews in the UK and elsewhere are concerned about antisemitism. But it is evident that more work needs to be done to understand the targets of this concern – where the threats lie, and the nature and scale of the problems that exist.
In general, the report maintains that research data on antisemitism in the UK vary in quality, and despite a recent flurry of research activity, many of the outputs seem to generate far more heat than light. We argue that much more work needs to be done in coordinating research efforts, maximising the value of existing datasets, focusing on the areas of greatest concern, and ensuring that any data collected and analysed are strongly concentrated on the most important policy questions: understanding the threat, and providing genuine policy insights for international, national and Jewish communal leaders, as well as Jews more generally.
