Unlocking the microblogging potential for science and medicine

Abstract

Twitter is one of the most popular microblogging and social networking services, where users can post, retweet, comment, and engage in collaborative discussions. However, improper usage of Twitter can be detrimental to science and even have a negative impact on mental health. Thus, analyzing tweets and Twitter data of various researchers will help us to deduce appropriate ways of using Twitter to advance in our research careers. Existing literature has analyzed the activity of scientists on Twitter, such as studying the relationship between Twitter mentions and article citations, determining the benefits of Twitter in the development and distribution of scientific knowledge, relevant metrics for prediction of highly cited articles, and type of content that researchers tweet etc. For example, Eysenbach et al performed an analysis of tweets and citations and how one can predict citations using tweets. Most of the existing literature analyzed a limited number of researchers, compromising the generalizability of derived results. In our study, we have taken a comprehensive and systematic approach to analyze 167,000 scientists who published research papers on PubMed using data-driven methods. We observed various parameters like number of followers, number of friends, citation count and K-index, in the light of gender, ancestry and profession of the researchers.