Boetto, E., Fantini, M. P., Gangemi, A., Golinelli, D., Greco, M., Nuzzolese, A. G., ... & Rallo, F. (2020). Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19. Scientometrics, 1-27. https://link.springer.com/article/10.1007/s11192-020-03809-7 

University of Michigan - Ann Arbor

- Interested in studying what communication mediums are most effective for early COVID-19 research and communication and the extent to which altmetric data can assess the impact of scientific research on COVID-19
- Studied 212 scientific publications on COVID-19 published between January 15 and February 24, 2020
- Found a moderate correlation between citation count and citations and mentions on social media
- Twitter, Facebook, news and blogs, and citations in academic publications are all sources of scholarly communication about COVID-19

Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19

- Studied 212 scientific publications on COVID-19 published between January 15 and February 24, 2020
- First looked at title and abstract to exclude irrelevant publications
- Then obtained full text versions of relevant publications
- Publications on other coronaviruses also excluded
- Identified DOIs for chosen papers using Crossref Metadata API in order to gather citation and altmetric data

Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19 data collection

- Density estimation
- Correlation analysis
- Comprehensive impact score (CIS)

Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19 data analysis

- Citations, social media, and mentions are all correlated, regardless of the indicators used 
- Correlation between citations and usage (Mendeley readers) also found 
- Social media sharing, news mentions, and citations in academic papers all contributed to research communication on COVID-19 and have the highest comprehensive impact scores 

Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19 discussion - behavioral perspective and impact analysis 

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