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Data Mining and Content Analysis of Chinese Social Media Platform Weibo During Early COVID-19 Outbreak: A Retrospective Observational Infoveillance Study.

BACKGROUND: Coronavirus disease 2019 (COVID-19), which began in Wuhan, China in December 2019, is a rapidly spreading global pandemic with over 1.9 million cases globally as of mid-April 2020. Infoveillance approaches using social media can help characterize disease distribution and public knowledge, attitudes, and behaviors critical to the early stages of an outbreak.

OBJECTIVE: To conduct a quantitative and qualitative assessment of Chinese social media posts originating in Wuhan City on the Chinese microblogging platform Weibo during the early stages of the COVID-19 outbreak.

METHODS: Chinese-language messages from Wuhan were collected for 39 days between December 23, 2019-January 30, 2020 on Weibo. For quantitative analysis, the total daily cases of COVID-19 in Wuhan were obtained from the Chinese National Health Commission and regression was used to fit a linear model to determine if Weibo COVID-19 posts were predictive of the number of cases reported. Qualitative content analysis used and inductive manual coding approach to identify parent classifications of news and user generated COVID-19 topics.

RESULTS: 115,299 Weibo posts were collected during the study time frame consisting of an average of 2,956 posts per day (min 0; max 13,587). Quantitative analysis found a positive correlation between the number of Weibo posts and number of reported cases from Wuhan, with approximately 10 more COVID-19 cases per 40 social media posts (p < 0.001). This effect size was also larger than what was observed for the rest of China excluding Hubei provenance (where Wuhan is the capital city) and also held when comparing the number of Weibo posts to the incidence proportion of cases in Hubei province. Qualitative analysis of 11,893 posts during the first 21-days of the study period uncovered four parent classifications including Weibo discussions about the causative agent of the disease, changing epidemiological characteristics of the outbreak, and public reaction to outbreak control and response measures. Generally, these themes also exhibited public uncertainty and changing knowledge and attitudes about COVID-19, including posts exhibiting both protective and higher-risk behavior.

CONCLUSIONS: Results of this study provide initial insight into the origins of the COVID-19 outbreak based upon quantitative and qualitative analysis of Chinese social media data at the early epicenter in Wuhan city. Future studies should continue to explore the utility of social media data to predict COVID-19 disease severity, measure public reaction and behavior, and evaluate effectiveness of outbreak communication.

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