[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-150618-en":3,"doc-seo-150618-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},150618,1374391974564,"Clementine","https://ap-avatar.wpscdn.com/avatar/14000253aa45c000a9e?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779874745381141002",8,"Research & Report","Decoding Antisemitism: An AI-driven Study on Hate Speech and Imagery Online - Pilot Project - August 2021","The second Discourse Report from the Decoding Antisemitism pilot project applies AI-driven analysis to more than 15,000 online comments from leading mainstream media outlets in Great Britain, France, and Germany. Findings confirm that escalation in the Arab-Israeli conflict acts as a central facilitator for antisemitic expressions, with distinct prevalence across the three national datasets. Web commentary on the Israeli vaccination campaign also shows how unrelated media stories can enable antisemitic ideas and stereotypes. The report further examines national accusations against prominent individuals, highlighting the adaptability of antisemitism and its role in constructing enemy images targeting rival groups, elites, and minorities. Coded datasets are designed as training material for subsequent machine-learning classifiers.","Discourse Report | 2  \nPilot Project  \nDecoding Antisemitism: An AI-driven Study on Hate Speech and Imagery Online  \nPrincipal Investigator:  \nDr Matthias J. Becker  \nCentre for Research on Antisemitism, TU Berlin  \nCo-Investigator: Dr Daniel Allington  \nDepartment of Digital Humanities, King’s College London  \nTU Research Team: Dr Laura Ascone  \nDr Matthew Bolton Alexis Chapelan Dr Jan Krasni Karolina Placzynta Marcus Scheiber Hagen Troschke Chloé Vincent  \nProject Manager: Prof Uffa Jensen  \nCentre for Research on Antisemitism, TU Berlin  \nFunded by the Alfred Landecker Foundation  \nAugust 2021  \nProject Coordination:  \nDr. Susanne Beer (Project Coordinator)  \nJonas Greiner (Secretary)  \nTU Berlin  \nCentre for Research on Antisemitism (ZfA) Kaiserin-Augusta-Allee 104–106 10553 Berlin  \nContact: [info@decoding-antisemitism.eu](info@decoding-antisemitism.eu)  \n[Web:](Web: decoding-antisemitism.eu)[ ](Web: decoding-antisemitism.eu)[decoding-antisemitism.eu](Web: decoding-antisemitism.eu)  \nAdvisory Board:  \nProf Johannes Angermuller, Discourse, Languages and Applied Linguistics, The Open University, UK Dr Ildikó Barna, Department of Social Research Methodology, Eötvös Loránd University, Budapest, Hungary Prof Michael Butter, American Literary and Cultural History, Eberhard Karl University of Tübingen, Germany Prof Manuela Consonni, Vidal Sassoon International Center for the Study of Antisemitism, Hebrew University, IL Prof Niva Elkin-Koren, Faculty of Law, Tel Aviv University, IL  \nProf Martin Emmer, Institute for Media and Communication Studies, FU Berlin; Weizenbaum Institute, Germany Prof David Feldman, Birkbeck Institute for the Study of Antisemitism, University of London, UK  \nDr Joel Finkelstein, Network Contagion Research Institute; Princeton University, USShlomi Hod, HIIG’s AI & Society Lab, Berlin, Germany  \nProf Günther Jikeli, Institute for the Study of Contemporary Antisemitism, Indiana University Bloomington, US  \nDr Lesley Klaff, Department of Law & Criminology, Sheffield Hallam University, UK Prof Jörg Meibauer, Johannes Gutenberg Universität Mainz, Germany Dr Andre Oboler, Online Hate Prevention Institute, AUS  \nProf Martin Reisigl, Department of Linguistics, Universität Wien, Austria  \nProf Eli Salzberger, The Minerva Center for the Rule of Law under Extreme Conditions, University of Haifa, IL Robert Schwarzenberg, German Research Centre for Artificial Intelligence (DFKI), Berlin, Germany  \nDr Charles A. Small, Institute for the Study of Global Antisemitism and Policy; St Antony’s College, University of Oxford, UK Dr Abe Sweiry, Home Office UK  \nProf Gabriel Weimann, Department of Communication, University of Haifa, IL Dr Mark Weitzman, Simon Wiesenthal Center, US  \nProf Harald Welzer, Norbert Elias Center for Transformation Design & Research (NEC), Europa-Universität Flensburg; Futurzwei. Stiftung Zukunftsfähigkeit, Germany  \nDr Juliane Wetzel, Centre for Research on Antisemitism (ZfA), TU Berlin, Germany  \nMichael Whine MBE, UK & Bureau Member, European Commission Against Racism and Intolerance, Council of Europe; European Jewish Congress, Belgien  \nProf Matthew L. Williams, Criminology; HateLab, Cardiff University, UK  \nTable of Contents  \nExecutive Summary 4  \n1. Introduction 5  \n2. Definition of Antisemitism and Operationalisation 7  \n3. Qualitative Analyses 9  \n3.1. Hamas-Israel conflict May 2021 9  \n3.1.1. UK 9  \n3.1.2. France 12  \n3.1.3. Germany 14  \n3.1.4. Summary 17  \n3.2. Covid-19 Vaccine Rollout in Israel 18  \n3.2.1. UK 18  \n3.2.2. France 20  \n3.2.3. Germany 22  \n3.2.4. Summary 24  \n3.3. Three Independent Case Studies 25  \n3.3.1. The Miller Case in the UK 25  \n3.3.2. The Dieudonné-Soral Case in France 27  \n3.3.3. The Maaßen Case in Germany 30  \n3.3.4. Summary 33  \n4. Quantitative Analysis 34  \n5. Summary & Outlook 38  \nAnnex 40  \nReferences 43  \nSources 44  \n4 Executive Summary  \nExecutive Summary  \nFor the second discourse report on the pilot project“Decoding Antisemitism,” the research team studie","cbCaidjNpEKjjD5q","https://ap.wps.com/l/cbCaidjNpEKjjD5q","pdf",1881108,1,47,"English","en",105,"# Executive Summary\n# 1. Introduction\n# 2. Definition of Antisemitism and Operationalisation\n# 3. Qualitative Analyses\n## 3.1. Hamas-Israel conflict May 2021\n## 3.2. Covid-19 Vaccine Rollout in Israel\n## 3.3. Three Independent Case Studies\n# 4. Quantitative Analysis\n# 5. Summary & Outlook\n# Annex\n# References\n# Sources","[{\"question\":\"What data sources and scope does the report analyze?\",\"answer\":\"The research team studied in detail more than 15,000 online comments, mainly from Facebook profiles of leading mainstream media outlets in Great Britain, France, and Germany.\"},{\"question\":\"How does the Arab-Israeli conflict escalation relate to antisemitic expressions?\",\"answer\":\"Results confirm the escalation phase functions as a central facilitator for antisemitic expressions, with antisemitic topoi present at 12.6% in the French, 13.6% in the German, and 26.9% in the British dataset.\"},{\"question\":\"What is the purpose of the coded datasets in the project?\",\"answer\":\"The datasets coded for the report are intended as first training material for classifiers during the machine learning phase of the project, supporting improved accuracy through ongoing development.\"}]","Decoding Antisemitism: An AI-driven Study on Hate Speech and Imagery Online - Pilot Project - August 2021 | PDF",1787823955,118,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"decoding-antisemitism-an-ai-driven-study-on-hate-speech-and-imagery-online-pilot-project-august-2021","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/decoding-antisemitism-an-ai-driven-study-on-hate-speech-and-imagery-online-pilot-project-august-2021/150618/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-27",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What data sources and scope does the report analyze?","Question",{"text":75,"@type":76},"The research team studied in detail more than 15,000 online comments, mainly from Facebook profiles of leading mainstream media outlets in Great Britain, France, and Germany.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the Arab-Israeli conflict escalation relate to antisemitic expressions?",{"text":80,"@type":76},"Results confirm the escalation phase functions as a central facilitator for antisemitic expressions, with antisemitic topoi present at 12.6% in the French, 13.6% in the German, and 26.9% in the British dataset.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the purpose of the coded datasets in the project?",{"text":84,"@type":76},"The datasets coded for the report are intended as first training material for classifiers during the machine learning phase of the project, supporting improved accuracy through ongoing development.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]