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Identifying collaboration dynamics of bipartite author-topic networks with the influences of interest changes

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Abstract

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.

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Acknowledgements

This work as parts of a dissertation about scholar profiles in expert recommendation system was funded by the Indonesia Endowment Fund for Education (LPDP in Indonesian) with the grant number PRJ-4228/LPDP.3/2016 of the LPDP Doctoral Scholarship Programme fiscal year 2017–2020. Some sections of the manuscript was prepared during September-December 2018 in University of Groningen, the Netherlands under Enhancing International Publication (EIP or PKPI in Indonesian) Program by Ministry of Research, Technology and Higher Education of the Republic of Indonesia (RISTEKDIKTI in Indonesian). Furthermore, this research was also partially funded by RISTEKDIKTI under World Class Universities (WCU) Program managed by Institut Teknologi Bandung, Indonesia in 2019.

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Correspondence to Diana Purwitasari.

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The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Purwitasari, D., Fatichah, C., Sumpeno, S. et al. Identifying collaboration dynamics of bipartite author-topic networks with the influences of interest changes. Scientometrics (2020) doi:10.1007/s11192-019-03342-2

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Keywords

  • Longitudinal network analysis
  • Scientific collaboration dynamics
  • Research interest changes
  • One mode co-author network
  • Bipartite (two-mode) author-topic network
  • Stochastic actor-oriented model

Mathematics Subject Classification

  • 68T30
  • 68U15
  • 90B15
  • 91B16
  • 91C20
  • 91D30

JEL Classification

  • C31
  • C38
  • C44
  • D80
  • D85