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Showing content from https://pubmed.ncbi.nlm.nih.gov/32936772/ below:

The Resurgence of Cyber Racism During the COVID-19 Pandemic and its Aftereffects: Analysis of Sentiments and Emotions in Tweets

Affiliations

• ¹ Jaipuria Institute of Management, Jaipur, India.

• PMID: 32936772
• PMCID: PMC7596656
• DOI: 10.2196/19833

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Akash Dutt Dubey. JMIR Public Health Surveill. 2020.

• ¹ Jaipuria Institute of Management, Jaipur, India.

• PMID: 32936772
• PMCID: PMC7596656
• DOI: 10.2196/19833

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Background: With increasing numbers of patients with COVID-19 globally, China and the World Health Organization have been blamed by some for the spread of this disease. Consequently, instances of racism and hateful acts have been reported around the world. When US President Donald Trump used the term "Chinese Virus," this issue gained momentum, and ethnic Asians are now being targeted. The online situation looks similar, with increases in hateful comments and posts.

Objective: The aim of this paper is to analyze the increasing instances of cyber racism during the COVID-19 pandemic, by assessing emotions and sentiments associated with tweets on Twitter.

Methods: In total, 16,000 tweets from April 11-16, 2020, were analyzed to determine their associated sentiments and emotions. Statistical analysis was carried out using R. Twitter API and the sentimentr package were used to collect tweets and then evaluate their sentiments, respectively. This research analyzed the emotions and sentiments associated with terms like "Chinese Virus," "Wuhan Virus," and "Chinese Corona Virus."

Results: The results suggest that the majority of the analyzed tweets were of negative sentiment and carried emotions of fear, sadness, anger, and disgust. There was a high usage of slurs and profane words. In addition, terms like "China Lied People Died," "Wuhan Health Organization," "Kung Flu," "China Must Pay," and "CCP is Terrorist" were frequently used in these tweets.

Conclusions: This study provides insight into the rise in cyber racism seen on Twitter. Based on the findings, it can be concluded that a substantial number of users are tweeting with mostly negative sentiments toward ethnic Asians, China, and the World Health Organization.

Keywords: COVID-19; China; Twitter; WHO; infodemic; infodemiology; pandemic; racism.

©Akash Dutt Dubey. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 15.10.2020.

PubMed Disclaimer

Conflicts of Interest: None declared.

Flowchart for sentiment analysis of…

Flowchart for sentiment analysis of tweets. API: application programming interface.

Flowchart for sentiment analysis of tweets. API: application programming interface.

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