Could early tweet counts predict later citation counts? A gender study in Life Sciences and Biomedicine (2014-2016).

ABSTRACT: In this study, it was investigated whether early tweets counts could differentially benefit female and male (first, last) authors in terms of the later citation counts received. The data for this study comprised 47,961 articles in the research area of Life Sciences & Biomedicine from 2014-2016, retrieved from Web of Science's Medline. For each article, the number of received citations per year was downloaded from WOS, while the number of received tweets per year was obtained from PlumX. Using the hurdle regression model, I compared the number of received citations by female and male (first, last) authored papers and then I investigated whether early tweet counts could predict the later citation counts received by female and male (first, last) authored papers. In the regression models, I co

SUBMITTER: Dehdarirad T 

PROVIDER: S-EPMC7605688 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature