(Jewish Group) Jewish pols experienced 6,000 antisemitic tweets in a month, says ADL
Jewish incumbents running for reelection were bombarded with antisemitism on Twitter over the summer, according to a study released Tuesday by the Anti-Defamation League.
The ADL found that between July 23 and August 22, 30 incumbent Jewish members of the House and Senate received a total of nearly 6,000 antisemitic tweets, about 10% of the tweets directed at the group as a whole.
Nearly half of the tweets questioned the loyalty, honesty, ideology or faith of Jewish incumbents, the report said. Other common themes included misinformation about Democratic donor George Soros, including conspiracy theories that he is bankrolling Black Lives Matter protests and “antifa” in order to support “Jewish supremacy;” allegations of Jewish control over the media, the financial world or the government; and accusations that incumbents were secret Communists or Marxists. Some of the tweets “targeted incumbents with claims of pedophilia,” a nod to a QAnon conspiracy theory that purports the government is running a child sex-trafficking ring.
“Social media platforms are breeding grounds for hate and antisemitism at a frightening scale, and as very public and sometimes polarizing figures, Jewish members of Congress often experience the worst of this on Twitter,” said ADL CEO Jonathan Greenblatt in a statement.
The majority of the tweets dealt in antisemitic tropes rather than direct anti-Jewish slurs, said the report; fewer than 10% of the tweets contained explicitly antisemitic language. Twitter has yet to remove any of those that do.
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Online Hate Index Report: The Digital Experience of Jewish Lawmakers
In late 2018, Pew Research Center reported that social media sites had surpassed print newspapers as a news source for Americans, when one in five U.S. adults reported that they often got news via social media.i By the following year, that figure had increased to 28% and the trend is only risingii. Combine that with a deeply divided polity headed into a bitterly divisive 2020 U.S. presidential election season and it becomes crucial to understand the information that Americans are exposed to online about political candidates and the topics they are discussing. It is equally important to explore how online discourse might be used to intentionally distort information and create and exploit misgivings about particular identity groups based on religion, race or other characteristics.
In this report, we are bringing together the topic of online attempts to sow divisiveness and misinformation around elections on the one hand, and antisemitism on the other, in order to take a look at the type of antisemitic tropes and misinformation used to attack incumbent Jewish members of the U.S Congress who are running for re-election. This analysis was aided by the Online Hate Index (OHI), a tool currently in development within the Anti-Defamation League (ADL) Center for Technology and Society (CTS) that is being designed to automate the process of detecting hate speech on online platforms. Applied to Twitter in this case study, OHI provided a score for each tweet which denote the confidence (in percentage terms) in classifying the subject tweet as antisemitic.
This study presents a snapshot in time of “Problematic” content, which for the purposes of this report we have defined as including both antisemitic tweets as well as tweets that include antisemitic tropes but require more context to be definitively categorized as antisemitic. The findings of this report are based on a review of 5,954 tweets directed at all 30 Jewish incumbents up for re-election on November 3, 2020. The tweets in our sample were all posted between July 23, 2020 to August 22, 2020.
The findings of this report, while limited, are alarming and, unfortunately, not surprising. We find distinct antisemitic tropes targeting Jewish incumbents, many of which have been recently amplified by QAnoniii, as well as other conspiracy theorists. For a full list of incumbents and details on OHI and methodology, please refer to the Methodology section.
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