How do scholars and non-scholars participate in dataset dissemination on Twitter

Abstract

Focusing on the dataset dissemination structure on Twitter, this study aims to investigate how users of two different identities, scholars and the public, participate in the dissemination process. We collected 2464 datasets from Altmetric.com and used social network analysis to plot the graphs. From a macroscopic viewpoint, most datasets were diffused by viral dissemination (structure II) and mixed dissemination (structure III), and the diffusion level was fundamentally one or two levels. Based on the topics clustering results of the datasets, the majority were about open access, research data, and Altmetrics, as well as astronomy, biology, medicine, and environmental engineering. The dataset dissemination structure shared a little relationship with the research topic. From the microscopic viewpoint of parent nodes and child nodes, during the dataset dissemination, there were only marginally more Twitter users with scholar status than non-scholar ones, suggesting that compared with traditional academic accomplishments such as journal papers. However, the dataset seems to be more professional and targeted; significant audience beyond academics are also involved. During disseminating datasets on Twitter, most tended to be diffused among users of the same identity. However, a few non-scholars played crucial roles, such as super users and intermediaries. Overall, a considerable part of tweets and tweets of parent nodes with the ability to spread is primarily the tweets commented simultaneously forwarded (type II) are posted at the same time commented. Hence, this study underlines the significance of research data-sharing and social media's role in public participation in science.