University of Michigan - Ann Arbor

Quantitative analysis
- Statistically significant positive relationship between posts and case counts
- Found the simple regression model to predict the percent increase in cases
- The number of daily Weibo posts is mostly a direct reflection in the number of cases, and this pattern is usually uninterrupted

Qualitative analysis 
- For parent identification, many similar terms were used due to the lack of uniformity in official names for the pandemic and other related terms 
- Had 4 parent groups – causes of disease, characteristics of outbreak, public response to outbreak, and response measures
- Discussion of outbreak causes changed as more information was found about this specific topic 
- Emergence of new themes most likely driven by official sources, such as government-provided information and the news 

Data mining and content analysis of the Chinese social media platform Weibo during the early COVID-19 outbreak: retrospective observational infoveillance study results

Li, J., Xu, Q., Cuomo, R., Purushothaman, V., & Mackey, T. (2020). Data mining and content analysis of the Chinese social media platform Weibo during the early COVID-19 outbreak: retrospective observational infoveillance study. JMIR public health and surveillance, 6(2), e18700. https://publichealth.jmir.org/2020/2/e18700/

Data mining and content analysis of the Chinese social media platform Weibo during the early COVID-19 outbreak: retrospective observational infoveillance study 

Data mining and content analysis of the Chinese social media platform Weibo during the early COVID-19 outbreak: retrospective observational infoveillance study longitudinal trends

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