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Accepted for/Published in: JMIR Infodemiology

Date Submitted: Jul 5, 2021
Date Accepted: Jan 22, 2022

The final, peer-reviewed published version of this preprint can be found here:

(Mis)Information on Digital Platforms: Quantitative and Qualitative Analysis of Content From Twitter and Sina Weibo in the COVID-19 Pandemic

Kreps S

(Mis)Information on Digital Platforms: Quantitative and Qualitative Analysis of Content From Twitter and Sina Weibo in the COVID-19 Pandemic

JMIR Infodemiology 2022;2(1):e31793

DOI: 10.2196/31793

PMID: 36406147

PMCID: 9642842

(Mis)Information on Digital Platforms: Lessons from Twitter and Sina Weibo in the COVID-19 Pandemic

  • Sarah Kreps

ABSTRACT

Background:

Misinformation about COVID-19 has presented challenges to public health authorities during pandemics. Understanding the prevalence and type of misinformation across contexts offers a way to understand the discourse around COVID-19 while informing potential countermeasures.

Objective:

The aim of the study was to study COVID-19 content on two prominent microblogging platform, Twitter, based in the United States, and Sina Weibo, based in China, and compare the content and relative prevalence of misinformation to better understand public discourse of public health issues across social media and cultural contexts.

Methods:

A total of 3,579,575 posts were scraped from both Weibo and Twitter, focusing on content from January 30th, 2020, when the World Health Organization (WHO) declared COVID-19 a “Public Health Emergency of International Concern” and February 6th, 2020. A 1% random sample of tweets that contained both the English keywords “coronavirus” and “covid-19” and the equivalent Chinese characters was extracted and analyzed based on changes in the frequencies of keywords and hashtags. Misinformation on each platform was compared by manually coding and comparing posts using the World Health Organization fact-check page to adjudicate accuracy of content.

Results:

Both platforms posted about the outbreak and transmission but posts on Sina Weibo were less likely to reference controversial topics such as the World Health Organization and death and more likely to cite themes of resisting, fighting, and cheering against the coronavirus. Misinformation constituted 1.1% of Twitter content and 0.3% of Weibo content.

Conclusions:

Quantitative and qualitative analysis of content on both platforms points to cross-platform differences in public discourse surrounding the pandemic and informs potential countermeasures for online misinformation.


 Citation

Please cite as:

Kreps S

(Mis)Information on Digital Platforms: Quantitative and Qualitative Analysis of Content From Twitter and Sina Weibo in the COVID-19 Pandemic

JMIR Infodemiology 2022;2(1):e31793

DOI: 10.2196/31793

PMID: 36406147

PMCID: 9642842

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