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Homophily versus preferential attachment: Evolutionary mechanisms of scientific collaboration networks

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  • Zhen-Zhen Wang

    (Web Mining Lab, Department of Media and Communication, City University of Hong Kong, Tat Chee Avenue Kowloon, Hong Kong SAR, Hong Kong)

  • Jonathan J. H. Zhu

    (Web Mining Lab, Department of Media and Communication, City University of Hong Kong, Tat Chee Avenue Kowloon, Hong Kong SAR, Hong Kong)

Abstract

Homophily and preferential attachment are among the most recognized mechanisms of network evolution. Instead of examining the two mechanisms separately, this study considers them jointly in a scholarly collaboration network. Specifically, when a new scholar enters a field, how does he/she choose the first collaborator from the pool of available scholars? We find that new scholars tend to collaborate with someone who works in the same institution (which is called constrained acceptance), shares similar specialty interests (active choice), or has already worked with many collaborators (random action). We view constrained acceptance and active choice as supporting evidence for homophily (because similarity is attractive) and random action as supporting evidence for preferential attachment (because popularity is attractive). As such, both homophily and preferential attachment affect the evolution of collaboration networks. Furthermore, the influences vary over time with random action, constrained acceptance, and active choice taking turns to act the dominant force at the beginning, middle and later phases of the evolution process, respectively.

Suggested Citation

  • Zhen-Zhen Wang & Jonathan J. H. Zhu, 2014. "Homophily versus preferential attachment: Evolutionary mechanisms of scientific collaboration networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(05), pages 1-8.
  • Handle: RePEc:wsi:ijmpcx:v:25:y:2014:i:05:n:s0129183114400142
    DOI: 10.1142/S0129183114400142
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    Cited by:

    1. Peng Liu & Liang Gui & Huirong Wang & Muhammad Riaz, 2022. "A Two-Stage Deep-Learning Model for Link Prediction Based on Network Structure and Node Attributes," Sustainability, MDPI, vol. 14(23), pages 1-15, December.
    2. Liu, Junwan & Guo, Xiaofei & Xu, Shuo & Song, Yinglu & Ding, Kaiyue, 2023. "A new interpretation of scientific collaboration patterns from the perspective of symbiosis: An investigation for long-term collaboration in publications," Journal of Informetrics, Elsevier, vol. 17(1).
    3. Sun, Yutao & Cao, Cong, 2018. "The evolving relations between government agencies of innovation policymaking in emerging economies: A policy network approach and its application to the Chinese case," Research Policy, Elsevier, vol. 47(3), pages 592-605.

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