Identifying diffusion patterns of research articles on Twitter: A case study of online engagement with open access articles. (January 2019)

• Record Type: Journal Article
• Authors: Alperin, Juan Pablo; Gomez, Charles J; Haustein, Stefanie
• Is Part Of: Public understanding of science. Volume 28:Number 1(2019)
• Page Start: 2
• Page End: 18
• Publication Date: 2019-01
• Subjects: altmetrics -- diffusion -- open access -- public use of research -- science communication -- social media -- social network analysis -- Twitter; Science news -- Periodicals; Science -- Social aspects -- Periodicals; 303.483
• DOI: 10.1177/0963662518761733
• Languages: English
• ISSNs: 0963-6625

Abstract

The growing presence of research shared on social media, coupled with the increase in freely available research, invites us to ask whether scientific articles shared on platforms like Twitter diffuse beyond the academic community. We explore a new method for answering this question by identifying 11 articles from two open access biology journals that were shared on Twitter at least 50 times and by analyzing the follower network of users who tweeted each article. We find that diffusion patterns of scientific articles can take very different forms, even when the number of times they are tweeted is similar. Our small case study suggests that most articles are shared within single-connected communities with limited diffusion to the public. The proposed approach and indicators can serve those interested in the public understanding of science, science communication, or research evaluation to identify when research diffuses beyond insular communities.