How do scholars and non-scholars participate in dataset dissemination on Twitter |
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| Institution: | 1. Department of Mathematics, Louisiana State University, Baton Rouge, LA, USA;2. Department of Mathematics and Statistics, Williams College, Williamstown, MA, USA;3. Graduate Program in Data Science, New College of Florida, Sarasota, FL, USA;4. Department of Experimental Statistics, Louisiana State University, Baton Rouge, LA, USA;1. Science Policy and Strategy Department Administrative Headquarters of the Max Planck Society, Hofgartenstr. 8, 80539 Munich, Germany;2. Ludwig-Maximilians-Universität Munich, Department of Sociology, Konradstr. 6, 80801 Munich, Germany;1. School of Information Management, Nanjing University, Nanjing, Jiangsu Province 210093, China;2. School of Journalism and Communication, Hunan University, Changsha, Hunan Province 410082, China;1. Department of Physics, University of Thessaloniki, and Center of Complex Systems, Thessaloniki 54124, Greece;2. Department of Physics, Bar-Ilan University, Ramat-Gan 52900, Israel;1. Department of Library and Information Science Education, College of Education, Kongju National University, Gongju 32588, Republic of Korea;2. Department of Library and Information Science, Hannam University, Daejeon 34430, Republic of Korea;3. Department of Library and Information Science, Cheongju University, Cheongju 28503, Republic of Korea;4. Department of Library and Information Science, Yonsei University, Seoul 03722, Republic of Korea;1. Department of Computer Science, University of Pisa, and IIT-CNR of Pisa, Italy;2. Department of Economics and Statistics, University of Siena, Italy;3. Université du Québec à Trois-Riviéres, Canada;4. Université du Québec à Montreal, Canada |
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| 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. |
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