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Network and community structure in a scientific team with high creative performance

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  • Li, Jingjing
  • Zhang, Jian
  • Li, Huajiao
  • Jiang, Meihui

Abstract

Current studies have indicated that the type and intensity of the relations in a social network can impact individuals’ creative performance. However, it is more practical to explore how to improve team’s creative performance from the perspective of network and community structure. We conduct a survey of a real scientific team network, in which each team member chooses five members (s)he regards as his (her) friends, five members (s)he always works with, and five members (s)he wants to work with. The members were asked to rank the five members they selected according to their closeness. We derived three networks: a friend network, a real cooperation network and a desired cooperation network. Additionally, we have constructed a directed-weighted network with the team members as nodes, the relations (friend, real cooperation, and cooperation desire) between members as edges, and the closeness of these relations as weights. The main results show the following. (1) This scientific team is a leader network with nodes with weighted degrees significantly larger than those of other nodes. The weighted in-degree sequence and the weighted out-degree sequence have different properties. (2) Creative performance is higher for the leader communities than for the self-organized communities. After removing the leader nodes of the leader communities, creative performance in the communities and in the whole network decreased. (3) Quadratic assignment procedure correlation (QAP) analysis shows that the similarity between the real cooperation network and the desired cooperation network is lowest in self-organized communities, and the creative performance is low if the similarity between the two networks is low; (4) creative performance is lower in a network that only takes into account the desired cooperation of members. This study sheds light on the potential application of complex networks in the issues of group division and team construction in the workplace and in the field of education.

Suggested Citation

  • Li, Jingjing & Zhang, Jian & Li, Huajiao & Jiang, Meihui, 2018. "Network and community structure in a scientific team with high creative performance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 702-709.
    • Handle: RePEc:eee:phsmap:v:508:y:2018:i:c:p:702-709
    DOI: 10.1016/j.physa.2018.05.091
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    References listed on IDEAS

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    1. Cardillo, Alessio & Scellato, Salvatore & Latora, Vito, 2006. "A topological analysis of scientific coauthorship networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 372(2), pages 333-339.
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    Cited by:

    1. Chen, Shenwen & Ren, Siqiao & Zheng, Lei & Yang, Hanxin & Du, Wenbo & Cao, Xianbin, 2022. "A comparison study of educational scientific collaboration in China and the USA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).

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