University of Michigan - Ann Arbor

- Co-occurrence network of terms in tweets versus the original contents in the publications
- 601 most relevant terms are shown, making up 5 clusters of Twitter discussion topics regarding COVID-19-related research and publications
- Each term was assigned the average post date score
- Clusters 1 (clinical characteristics and transmission risks) and 3 (comparisons with other viruses) are depicted in lighter colors to indicate that these terms were mentioned towards the beginning of the outbreak
- Clusters 2 (clinical trials and potential treatments), 4 (virus persistence under different circumstances), and 5 (governmental measures and social responses) are shown in darker colors to demonstrate a gradual shift in attention to these topics for further research
- Also looked at 219 hashtags each mentioned at least 50 times
- In the earlier stages, Twitter users focused on COVID-19 in China, and later transitioned to hashtags associated with healthcare measures 

Tracking the Twitter attention around the research efforts on the COVID-19 pandemic results - Twitter discussions on COVID-19-related research

Fang, Z., & Costas, R. (2020). Tracking the Twitter attention around the research efforts on the COVID-19 pandemic. arXiv preprint arXiv:2006.05783. https://arxiv.org/abs/2006.05783 

Tracking the Twitter attention around the research efforts on the COVID-19 pandemic

Tracking the Twitter attention around the research efforts on the COVID-19 pandemic results - Twitter discussions on COVID-19-related research visualization

Learn Before

Related