University of Michigan - Ann Arbor

- Used co-occurrence network to display the 145 most relevant terms 
- 3 clusters generated- epidemiological, virological, and clinical research 
- Out of the clusters, clinical research publications received most Twitter attention 
- 45.3% of the tweets had a cosine similarity score between 0 and 0.1; 74% of Twitter mentions had a cosine similarity score below 0.5
- Low levels of similarity can be attributed to additional information being shared on Twitter rather than simply repeating information presented in publications
- Many Twitter mentions included longer texts, opinions, and attitudes in addition to scientific information 

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

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 - COVID-19 research topics mentioned on Twitter cosine similarity scores


Tracking the Twitter attention around the research efforts on the COVID-19 pandemic results - COVID-19 research topics mentioned on Twitter visualization

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