QUANTIFYING HATE: A YEAR OF ANTI-SEMITISM ON TWITTER QUANTIFYING HATE A Year of Anti-Semitism on Twitter Introduction 1 Major Findings 2 Methodology 3 Detailed Findings 5 Prevalent Anti-Semitic Themes Harvey Weinstein and Jewish Sexual Predators 7 Rothschild Conspiracy Theories 8 Anti-Zionism and Anti-Semitism 10 QAnon 12 “Globalist” as Code Word for “Jew” 14 Holocaust Denial 15 False Flags 17 George Soros 21 Recommendations 23 Quantifying Hate: A Year of Anti-Semitism on Twitter was conducted by ADL’s Center on Extremism. The Center on Extremism (COE) is a foremost authority on extremism, terrorism, anti-Semitism and all forms of hate. The COE’s team of investigators and analysts strategically monitors and exposes extremist movements and individuals, using cutting-edge technology to track real-time developments and provide actionable intelligence and data-based analysis to law enforcement, public officials, community leaders and technology companies. INTRODUCTION It’s nearly impossible to overstate the impact social media has on our world. That influence is often wielded in the service of good — think viral fund-raising efforts or protecting democratic movements against authoritarian threats — but it also can powerfully amplify society’s most dangerous attitudes. Racism, sexism, homophobia, religious extremism and conspiracy theories have deep roots in social media, and perpetrators have recognized and capitalized on the near-universal reach of popular platforms. This report is an effort to gauge the prevalence of one of these destructive prejudices — anti-Semitism — on one social media platform: Twitter — by examining the one-year period from January 29, 2017 to January 28, 2018. ADL frequently fields reports from constituents who describe an atmosphere of anti- Semitism on Twitter, including harassment from anti-Semitic trolls. We issued previous studies on this phenomenon. Media reports reflect this phenomenon as well. Experts at the ADL’s Center on Extremism (COE) wanted to go beyond those reports, to understand the problem in greater detail while examining tweets for nuance and context. How many anti- Semitic tweets are posted on Twitter during any given week? How do we know the tweets truly are anti-Semitic? What if some of these tweets are intended to convey an ironic or critical message? Using a proprietary, wide-ranging query, as well as statistical methods and expert analysis, COE analysts were able to determine that roughly 4.2 million anti-Semitic tweets were posted and reposted on Twitter in the one-year period specified above. We estimate that the tweets were issued by approximately three million unique handles. Of course, 4.2 million tweets is a very small number out of the trillions of tweets sent on the platform each year. But that does not negate the lived experience of Jews who have found Twitter to be a toxic environment. This number is still large enough to underscore the powerful harassment that exists and the ease with which a relative handful of users can infect our shared social media environment with negative stereotypes and conspiracy theories about Jews. This report, and the random statistical sample of over 55,000 carefully reviewed tweets which it generated, also will be useful to those designing artificial intelligence-based efforts to counter anti-Semitism and bigotry online. ADL already works with Twitter to help them address anti-Semitism and other forms of bigotry on their platform, and we know this is a difficult challenge to solve. We are proud to be part of Twitter’s Trust and Safety Council and to partner with Twitter as a member of our Problem Solving Lab to explore engineering-based approaches to address online hate and harassment. We already have seen the company make real progress on these issues and demonstrate leadership among social media platforms. And yet, despite recent advancements, intolerance on public platforms like Twitter still endures. It degrades the conversation and poisons the public discourse for all. Even a proportionally small number of Tweets that express anti-Semitism is too many, and any ADL CENTER ON EXTREMISM REPORT 1 platform that hosts such hate must ensure that it is using all means necessary to tackle the METHODOLOGY situation even as it seeks to balance legitimate concerns about not inhibiting freedom of expression. For this reason, this report includes not only a detailed review of our findings but 1. Process a set of recommendations for Twitter to take into consideration as it attempts to address The current findings are based on a complex Boolean query designed to identify language the issue and improve its performance. frequently used by anti-Semites. The query was broadly written to encompass obvious expressions of anti-Semitism, including classic anti-Semitic stereotypes; code words and We look forward to continuing to work with Twitter — and other platforms that seek our symbols sometimes used in an anti-Semitic fashion; and also subtle references to anti- help — to ensure these environments are a safe space for all users, regardless of their faith, Semitic conspiracy theories. race or other immutable attributes. Experts at ADL’s Center on Extremism assessed statistically significant samples of the tweets captured by this query for each week. The assessments were designed to identify the percentage of tweets not intended to express anti-Semitic sentiment or disseminate MAJOR FINDINGS anti-Semitic conspiracy theories. Of particular interest were tweets that used or cited anti- Semitic language in order to condemn it, or that used anti-Semitic language ironically. In As a result of a pilot research project, the Anti-Defamation League can estimate that these cases, analysis of the thread context (as well as accompanying videos and images) a minimum of approximately 4.2 million English language anti-Semitic tweets were was critical. Occasionally, the self-reported info in the tweeter’s “bio” field was also consulted disseminated between January 29, 2017 and January 28, 2018. The analysis showed that to help determine intent. When ADL experts were not reasonably confident that a given within predefined seven-day periods, the number of tweets expressing anti-Semitic tweet was anti-Semitic, it was marked as not containing anti-Semitic sentiment. A sufficient sentiment ranged from a low of 36,800 in week 26 (July 23-29) to a high of 181,700 in week number of tweets were assessed for each time period to result in a 3% margin of error. 45 (December 03-09). The average number of tweets expressing anti-Semitic sentiment The resulting percentage of anti-Semitic tweets in the representative sample was then throughout all 52 weeks of the analysis was 81,400. extrapolated back to the entire population of tweets pulled in by the query for its time period. This yielded the number of anti-Semitic tweets reported in the findings. NUMBER OF ANTI-SEMITIC TWEETS, This project is ADL’s second attempt to assess the amount of anti-Semitism on Twitter. In an Anti-Semitic Number of Anti-Semitic Tweets October 2016 report, ADL used keywords correlating with anti-Semitism to assess the total JANUARYTweets 29, 2017 TOJanuary JANU 29,AR Y2017 28, to2018 January 28, 2018 number of tweets which could potentially contain anti-Semitic content that were directed 200,000 at journalists. The current report refines the methodology by moving beyond simple keyword detection and estimating the number of instances of actual anti-Semitic sentiment 150,000 or content. The current report also expands the scope of the first study to address anti- Semitism in all English language tweets. A third project, the Online Hate Index being developed by ADL’s Center on Technology 100,000 and Society, has experimented with artificial intelligence and machine learning to detect the presence of hate speech on selected Reddit forums. The current project focuses solely 50,000 on anti-Semitism, including difficult-to-detect anti-Semitic conspiracy theories, and was designed and implemented by human experts without any automation or machine learning. ADL hopes that the project’s resulting corpus of tweets — which have been evaluated for WEEK 1 2345678910 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 MONTH JAN. FEB.MAR.MAPR. AY JUN. JUL. AUG. SEP.NOCT. OV.JDEC. AN. anti-Semitism — will be useful in training machine learning engines to detect anti-Semitism. 2 QUANTIFYING HATE ADL CENTER ON EXTREMISM REPORT 3 2. Defining Anti-Semitism DETAILED FINDINGS The current report is based on a proprietary Boolean query designed by experts at 1. Results of the Analysis ADL’s Center on Extremism. The query is designed to detect anti-Semitic content in the The query for this study was designed to be broad enough to return all results that could following categories: conceivably be anti-Semitic. This is why subsequent evaluation by human experts was so 1. Classic anti-Semitic stereotypes (e.g. references to Jews as greedy; controllers of important (i.e. to weed out all of the non-anti-Semitic tweets that we knew would be pulled banks, media, governments and academia; under-miners of culture and racial purity; in). From February 1, 2017 to Jan 28, 2018, our query pulled in almost nineteen million tweets, cursed for killing Jesus; etc.) with weekly figures ranging from 183,000 (week 30: July 23–29) to more than one million 2. Positive references to or promotion of known anti-Semitic personalities, authors, books, tweets (week 33: Aug 13–19). articles, videos and podcasts We then subjected a random, statistical sampling of more than 1,000 tweets per week 3. References to anti-Semitic conspiracy theories (e.g.