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Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data.

Tung Manh Ho1,2, Ha Viet Nguyen2, Thu-Trang Vuong3

  • 1Institute of Philosophy , Vietnam Academy of Social Sciences, Hanoi , 100000, Vietnam.

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Vietnamese social scientists exhibit sparse collaboration networks with high clustering, indicating inefficient knowledge sharing and low scientific output. This network structure is also fragile, highlighting the influence of a few key researchers.

Keywords:
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Area of Science:

  • Social Sciences
  • Bibliometrics
  • Network Analysis

Background:

  • Scientific collaboration is prevalent among Vietnamese scientists, yet detailed insights remain limited.
  • Social network analysis (SNA) offers a powerful lens to examine scientific communities globally.
  • SNA can illuminate the structure and dynamics of Vietnam's scientific landscape.

Purpose of the Study:

  • To analyze the collaboration patterns of Vietnamese social scientists using network theory.
  • To identify key characteristics of the Vietnamese social science research network.
  • To compare the overall network with its major components.

Main Methods:

  • Employed network theory to analyze a dataset of 412 Vietnamese social scientists.
  • Utilized Scopus database for identifying indexed publications.
  • Calculated network density and clustering coefficient for the entire network and its largest components.

Main Results:

  • The network exhibits very low density (0.47%) and high clustering (58.64%), suggesting inefficient information dissemination.
  • The network's vulnerability to the removal of highly connected individuals was observed.
  • The two largest network components, led by productive researchers, differed in network measures from the overall network.

Conclusions:

  • High clustering and low density correlate with inefficient expertise dissemination and potentially lower scientific output among Vietnamese social scientists.
  • The network's low robustness underscores the critical role of a few highly connected, productive researchers.
  • An intellectual elite within the network demonstrates potential for significant scientific contribution.