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A new method to construct co-author networks

Author

Listed:
  • Liu, Jie
  • Li, Yunpeng
  • Ruan, Zichan
  • Fu, Guangyuan
  • Chen, Xiaowu
  • Sadiq, Rehan
  • Deng, Yong

Abstract

In this paper, we propose a new method to evaluate the importance of nodes in a given network. The proposed method is based on the PageRank algorithm. However, we have made necessary improvements to combine the importance of the node itself and that of its community status. First, we propose an improved method to better evaluate the real impact of a paper. The proposed method calibrates the real influence of a paper over time. Then we propose a scheme of evaluating the contribution of each author in a paper. We later develop a new method to combine the information of the author itself and the structure of the co-author network. We use the number of co-authorship to calculate the effective distance between two authors, and evaluate the strength of their influence to each other with the law of gravity. The strength of influence is used to build a new network of authors, which is a comprehensive topological representation of both the quality of the node and its role in network. Finally, we apply our method to the Erdos co-author community and AMiner Citation Network to identify the most influential authors.

Suggested Citation

  • Liu, Jie & Li, Yunpeng & Ruan, Zichan & Fu, Guangyuan & Chen, Xiaowu & Sadiq, Rehan & Deng, Yong, 2015. "A new method to construct co-author networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 29-39.
    • Handle: RePEc:eee:phsmap:v:419:y:2015:i:c:p:29-39
    DOI: 10.1016/j.physa.2014.10.006
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    References listed on IDEAS

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    Cited by:

    1. Ricardo Lopes Andrade & Maísa Mendonça Silva & Leandro Chaves Rêgo, 2023. "A Scientometric and Social Network Analysis of the Literature on the Graph Model for Conflict Resolution," Group Decision and Negotiation, Springer, vol. 32(5), pages 1061-1082, October.
    2. Sheikhahmadi, Amir & Nematbakhsh, Mohammad Ali & Shokrollahi, Arman, 2015. "Improving detection of influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 833-845.
    3. Jun Zhang & Zhaolong Ning & Xiaomei Bai & Xiangjie Kong & Jinmeng Zhou & Feng Xia, 2017. "Exploring time factors in measuring the scientific impact of scholars," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1301-1321, September.
    4. Duan, Shuyu & Wen, Tao & Jiang, Wen, 2019. "A new information dimension of complex network based on Rényi entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 529-542.
    5. Park, Alex & Lappas, Petros, 2017. "Evaluating demand charge reduction for commercial-scale solar PV coupled with battery storage," Renewable Energy, Elsevier, vol. 108(C), pages 523-532.
    6. Hu, Jiantao & Du, Yuxian & Mo, Hongming & Wei, Daijun & Deng, Yong, 2016. "A modified weighted TOPSIS to identify influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 73-85.
    7. Noémi Gaskó & Rodica Ioana Lung & Mihai Alexandru Suciu, 2016. "A new network model for the study of scientific collaborations: Romanian computer science and mathematics co-authorship networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 613-632, August.

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