An analysis of COVID-19 article dissemination by Twitter compared to citation rates | medRxiv
DHopf's bookmarks 2022-01-28
Background The COVID-19 pandemic has resulted in over 1,000,000 cases across 181 countries worldwide. The global impact of COVID-19 has resulted in a surge of related research. Researchers have turned to social media platforms, namely Twitter, to disseminate their articles. The online database Altmetric is a tool which tracks the social media metrics of articles and is complementary to traditional, citation-based metrics. Citation-based metrics may fail to portray dissemination accurately, due to the lengthy publication process. Altmetrics are not subject to this time-lag, suggesting that they may be an effective marker of research dissemination during the COVID-19 pandemic. Objectives To assess the dissemination of COVID-19 articles as measured by Twitter dissemination, compared to traditional citation-based metrics, and determine article characteristics associated with tweet rates. Methods COVID-19 articles obtained from LitCovid published between January 1st to March 18th, 2020 were screened for inclusion. The following article characteristics were extracted independently, in single: Topic (General Info, Mechanism, Diagnosis, Transmission, Treatment, Prevention, Case Report, and Epidemic Forecasting), open access status (open access and subscription-based), continent of corresponding author (Asia, Australia, Africa, North America, South America, and Europe), tweets, and citations. A sign test was used to compare the tweet rate and citation rate per day. A negative binomial regression analysis was conducted to evaluate the association between tweet rate and article characteristics of interest. Results 1328 articles were included in the analysis. Tweet rates were found to be significantly higher than citation rates for COVID-19 articles, with a median tweet rate of 1.09 (IQR 6.83) tweets per day and median citation rate of 0.00 (IQR 0.00) citations per day, resulting in a median of differences of 1.09 (95% CI 0.86-1.33, P < .001). 2018 journal impact factors were positively correlated with tweet rate (P < .001). The topics Diagnosis (P = .01), Transmission (P < .001), Treatment (P = .01), and Epidemic Forecasting (P < .001) were positively correlated with tweet rate, relative to Case Report. The following continents of the corresponding author were negatively correlated with tweet rate, Africa (P < .001), Australia (P = .03), and South America (P < .001), relative to Asia. Open access journals were negatively correlated with tweet rate, relative to subscription-based journals (P < .001). Conclusions COVID-19 articles had significantly higher tweets rates compared to citation rates. This study further identified article characteristics that are correlated with the dissemination of articles on Twitter, such as 2018 journal impact factor, continent of the corresponding author, topic, and open access status. This highlights the importance of altmetrics in periods of rapidly expanding research, such as the COVID-19 pandemic to localize highly disseminated articles.