Identifying collaboration dynamics of bipartite author-topic networks with the influences of interest changes
Autor: | Diana Purwitasari, Christian Steglich, Surya Sumpeno, Chastine Fatichah, Mauridhi Hery Purnomo |
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Přispěvatelé: | Sociology/ICS |
Rok vydání: | 2020 |
Předmět: |
One mode co-author network
Computer science Research interest changes Library and Information Sciences 050905 science studies computer.software_genre ARTICLES Selection (linguistics) Bipartite (two-mode) author-topic network Longitudinal network analysis 2-MODE Driving factors Social network business.industry 05 social sciences General Social Sciences SCIENCE Data science Stochastic actor-oriented model Computer Science Applications SCIENTISTS Metadata Information extraction Dynamics (music) Publishing Scientific collaboration dynamics 0509 other social sciences 050904 information & library sciences business computer Network analysis |
Zdroj: | Scientometrics, 122(3), 1407-1443. SPRINGER |
ISSN: | 1588-2861 0138-9130 |
DOI: | 10.1007/s11192-019-03342-2 |
Popis: | Knowing driving factors and understanding researcher behaviors from the dynamics of collaborations over time offer some insights, i.e. help funding agencies in designing research grant policies. We present longitudinal network analysis on the observed collaborations through co-authorship over 15 years. Since co-authors possibly influence researchers to have interest changes, by focusing on researchers who could become the influencer, we propose a stochastic actor-oriented model of bipartite (two-mode) author-topic networks from article metadata. Information of scientific fields or topics of article contents, which could represent the interests of researchers, are often unavailable in the metadata. Topic absence issue differentiates this work with other studies on collaboration dynamics from article metadata of title-abstract and author properties. Therefore, our works also include procedures to extract and map clustered keywords as topic substitution of research interests. Then, the next step is to generate panel-waves of co-author networks and bipartite author-topic networks for the longitudinal analysis. The proposed model is used to find the driving factors of co-authoring collaboration with the focus on researcher behaviors in interest changes. This paper investigates the dynamics in an academic social network setting using selected metadata of publicly-available crawled articles in interrelated domains of "natural language processing" and "information extraction". Based on the evidence of network evolution, researchers have a conformed tendency to co-author behaviors in publishing articles and exploring topics. Our results indicate the processes of selection and influence in forming co-author ties contribute some levels of social pressure to researchers. Our findings also discussed on how the co-author pressure accelerates the changes of interests and behaviors of the researchers. |
Databáze: | OpenAIRE |
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