At the Extremes: The 2020 Election and American Extremism
In the weeks leading up to the 2020 presidential election, the ADL (Anti-Defamation League) Center on Extremism in conjunction with ADL’s Center for Technology and Society are releasing a series of news briefs on topics of concern regarding the role extremism plays in our current political environment.
Here's Part 3:
Conspiracy Theories and Anti-Asian Hostility on Twitter
Who/What: After President Trump announced his COVID-19 diagnosis, there was a surge of anti-Asian American and conspiracy theory content, often delving into antisemitism.
Why it Matters: the spread of xenophobic, racist or antisemitic conspiracy theories creates a dangerous political environment that could potentially result in harassment, discrimination, and even violence against targeted groups
On September 29, during the first presidential debate ahead of the 2020 U.S. election, President Donald Trump made inflammatory remarks regarding the COVID-19 virus that has killed over 210,000 Americans. “It’s China’s fault,” he said. “It should have never happened.” He also referred to COVID-19 as the “China plague.”
This was not the first time the president has cited China as responsible for the virus’s outbreak; he has been making similar comments since March. Earlier this year, as COVID-19 spread, public officials expressed anti-Chinese and anti-Asian hostility, which helped create and exacerbate a disturbing trend of harassment and violence against Asian Americans across the nation.
Just over two days after the debate, on October 2, President Trump tweeted shortly before 1:00 AM EDT that both he and First Lady Melania Trump tested positive for the COVID-19 virus. The ADL Center for Technology and Society (CTS) analyzed a subset of conversations on Twitter centered on the president’s announcement. CTS found that in the 12 hours following the tweet, the rate of language linked to anti-Asian hostility in this subset of conversations rose by approximately 85 percent. Hostility increased from an average of roughly 0.33 percent of tweets in this conversation before the tweet to an average of roughly 0.61 percent in the period after. From Oct. 2 to 5, the percentage of anti-Asian sentiment on Twitter in this subset of conversations remained elevated (roughly 0.60 percent of tweets in this subset of Twitter conversations).
In April, ADL reported on several prevalent conspiracy theories related to the COVID-19 pandemic, many of which were also present within the subset of conversations we analyzed. For example, the dataset contains numerous tweets falsely advancing the allegation that the coronavirus was engineered by humans, despite the fact that researchers studying the virus’s genetic makeup agree animals first transmitted the virus to humans. The more egregious conspiracy theories claim the virus is “patented”, a bioweapon, created by the Chinese government, or some combination of the three. Another conspiracy claim that gained traction holds Bill Gates responsible for the virus or involved in its spread.
These tools, while state of the art, are imperfect and still undergoing development to further increase accuracy. However, we believe the products and methods we used provide credible and helpful insights into how hate functions in digital social spaces. Reports such as Ziems et al. (2020), Ozalp et al. (2020) and Nguyen (2020), were generated with a similar methodology. In each case, the researchers used smaller human-annotated data sets to train a machine learning model to classify content as hateful or not. They then applied the classifier to a much larger dataset to gain insight into trends of online hate. As exemplified by these studies, this methodology is standard practice in this field.
Bertie Vidgen, Austin Botelho, David Broniatowski, Ella Guest, Matthew Hall, Helen Margetts, Rebekah Tromble, Zeerak Waseem, & Scott Hale. (2020). Detecting East Asian Prejudice on Social Media. arXiv:2005.03909 URL https://arxiv.org/abs/2005.03909
Nguyen, T.T.; Criss, S.; Dwivedi, P.; Huang, D.; Keralis, J.; Hsu, E.; Phan, L.; Nguyen, L.H.; Yardi, I.; Glymour, M.M.; Allen, A.M.; Chae, D.H.; Gee, G.C.; Nguyen, Q.C. Exploring U.S. Shifts in Anti-Asian Sentiment with the Emergence of COVID-19. Int. J. Environ. Res. Public Health 2020, 17, 7032
Ozalp, Sefa, et al. "Antisemitism on Twitter: Collective efficacy and the role of community organisations in challenging online hate speech." Social Media+ Society 6.2 (2020): 2056305120916850.
Ziems, Caleb, et al. "Racism is a Virus: Anti-Asian Hate and Counterhate in Social Media during the COVID-19 Crisis." arXiv preprint arXiv:2005.12423 (2020).
 We collected slightly more than 2.7 million tweets between 4:00pm EDT on Oct. 2 (approximately 5 hours before President Trump’s announcement) to 5:00pm EDT on Oct. 5 containing either at least one of the following mentions @realdonaldtrump, @potus @flotus @senatorloeffler or at least one of the following keywords: “trump”, “melania”, “first lady”, “china virus”, “plague”, “kung flu”, or “Wuhan”.