Corpus ID: 218889486

Racism is a Virus: Anti-Asian Hate and Counterhate in Social Media during the COVID-19 Crisis

@article{Ziems2020RacismIA,
  title={Racism is a Virus: Anti-Asian Hate and Counterhate in Social Media during the COVID-19 Crisis},
  author={C. Ziems and Bing He and Sandeep Soni and Srijan Kumar},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.12423}
}
The spread of COVID-19 has sparked racism, hate, and xenophobia in social media targeted at Chinese and broader Asian communities. However, little is known about how racial hate spreads during a pandemic and the role of counterhate speech in mitigating the spread. Here we study the evolution and spread of anti-Asian hate speech through the lens of Twitter. We create COVID-HATE, the largest dataset of anti-Asian hate and counterhate spanning three months, containing over 30 million tweets, and a… Expand
Predicting Anti-Asian Hateful Users on Twitter during COVID-19
We investigate predictors of anti-Asian hate among Twitter users throughout COVID-19. With the rise of xenophobia and polarization that has accompanied widespread social media usage in many nations,Expand
"A Virus Has No Religion": Analyzing Islamophobia on Twitter During the COVID-19 Outbreak
TLDR
CoronaBias dataset is presented, revealing the existence of anti-Muslim rhetoric around COVID-19 in the Indian sub-continent and the portrayal of religion as a symbol of patriotism played a crucial role in deciding how the Muslim community was perceived during the pandemic. Expand
From Fear to Hate: How A Pandemic Sparks Racial Animus in the United States
TLDR
It is found that the first local diagnosis of the Coronavirus leads to an immediate increase in racist Google searches and Twitter posts, with the latter mainly coming from existing Twitter users posting the slur for the first time. Expand
Detecting East Asian Prejudice on Social Media
TLDR
A new dataset and the creation of a machine learning classifier that categorizes social media posts from Twitter into four classes: Hostility against East Asia, Criticism of EastAsia, Meta-discussions of East Asian prejudice, and a neutral class are reported. Expand
On Analyzing COVID-19-related Hate Speech Using BERT Attention
TLDR
This work aims to discover the hate-related keywords linked to COVID-19 in hateful tweets posted on Twitter so that users posting such keywords can be asked to reconsider posting them and proposes a control mechanism wherein a user can be ask to reconsider using certain sensitive words identified by the approach. Expand
Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines
TLDR
This work presents and employs a methodological pipeline for assessing the links between hate speech and bot-driven activity through the lens of social cybersecurity, finding that bot activity is linked to higher hate in both countries, especially in communities which are denser and more isolated from others. Expand
Hate is the New Infodemic: A Topic-aware Modeling of Hate Speech Diffusion on Twitter
TLDR
This work crawls a large-scale dataset of tweets, retweets, user activity history, and follower networks, comprising over 161 million tweets from more than 41 million unique users, and proposes RETINA, a novel neural architecture that incorporates exogenous influence using scaled dot-product attention to predict the retweet dynamics of hateful content. Expand
Characterizing network dynamics of online hate communities around the COVID-19 pandemic
TLDR
A dynamic network framework to characterize hate communities is proposed, focusing on Twitter conversations related to COVID-19 in the United States and the Philippines, demonstrating that higher levels of community hate are consistently associated with smaller, more isolated, and highly hierarchical network clusters across both contexts. Expand
Countering hate on social media: Large scale classification of hate and counter speech
TLDR
An ensemble learning algorithm is used which pairs a variety of paragraph embeddings with regularized logistic regression functions to classify both hate and counter speech in a corpus of millions of relevant tweets from these two groups in Germany. Expand
Beyond a binary of (non)racist tweets: A four-dimensional categorical detection and analysis of racist and xenophobic opinions on Twitter in early Covid-19
TLDR
This research develops a fourdimensional category for racism and xenophobia detection, namely stigmatization, offensiveness, blame, and exclusion, and paves the way for the enactment of effective intervention policies to combat racist crimes and social exclusion under Covid-19. Expand
...
1
2
3
4
...

References

SHOWING 1-10 OF 105 REFERENCES
Spread of Hate Speech in Online Social Media
TLDR
This study performs the first cross-sectional view of how hateful users diffuse hate content in online social media on Gab and finds that the hateful users are far more densely connected among themselves. Expand
"Go eat a bat, Chang!": An Early Look on the Emergence of Sinophobic Behavior on Web Communities in the Face of COVID-19
TLDR
It is found that COVID-19 indeed drives the rise of Sinophobia on the Web and that the dissemination of Sinophobic content is a cross-platform phenomenon: it exists on fringe Web communities like \dspol, and to a lesser extent on mainstream ones like Twitter. Expand
In the Eyes of the Beholder: Sentiment and Topic Analyses on Social Media Use of Neutral and Controversial Terms for COVID-19
TLDR
Using sentiment feature analysis and topic modeling, substantial differences are revealed between the use of the controversial terms such as "Chinese virus" and that of the non-controversial termssuch as "COVID-19". Expand
Analyzing the hate and counter speech accounts on Twitter
TLDR
This paper analyzes hate speech and the corresponding counters (aka counterspeech) on Twitter and finds that the hate tweets by verified accounts have much more virality as compared to a tweet by a non-verified account. Expand
A first look at COVID-19 information and misinformation sharing on Twitter
TLDR
It is suggested that a meaningful spatio-temporal relationship exists between information flow and new cases of COVID-19, and while discussions about myths and links to poor quality information exist, their presence is less dominant than other crisis specific themes. Expand
COVID-19: The First Public Coronavirus Twitter Dataset
TLDR
A multilingual coronavirus (COVID-19) Twitter dataset that has been continuously collecting since January 22, 2020 is described and may contribute towards enabling informed solutions and prescribing targeted policy interventions to fight this global crisis. Expand
Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
TLDR
A list of criteria founded in critical race theory is provided, and these are used to annotate a publicly available corpus of more than 16k tweets and present a dictionary based the most indicative words in the data. Expand
Peer to Peer Hate: Hate Speech Instigators and Their Targets
TLDR
It is found that hate instigators target more popular and high profile Twitter users, and that participating in hate speech can result in greater online visibility, which advance the state of the art of understanding online hate speech engagement. Expand
Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment
I conduct an experiment which examines the impact of group norm promotion and social sanctioning on racist online harassment. Racist online harassment de-mobilizes the minorities it targets, and theExpand
The spread of low-credibility content by social bots
TLDR
It is found that bots play a major role in the spread of low-credibility content on Twitter, and control measures for limiting thespread of misinformation are suggested. Expand
...
1
2
3
4
5
...