CDIA: A Feasible Community Detection Algorithm Based on Influential Nodes in Complex Networks

  • Xinyu Huang
  • Dongming ChenEmail author
  • Tao Ren
  • Dongqi Wang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)


Community detection is a fundamental research in network science, which has attracted researchers all over the world to devoting into this work. However, the existing algorithms can hardly hold performance and efficiency simultaneously. Aiming at addressing the problem, and inspired by the force in physics, this paper defines the node influence from a network perspective. Afterwards, a novel approach to detect communities in terms of influential nodes is proposed. Furthermore, the vital nodes and overlapping nodes can be obtained. Series of experiments on synthetic and real-world networks are conducted, and the experimental results show that the proposed algorithm is capable and effective, which provides a reliable solution for analyzing network structure in-depth.


Influential nodes Nodes gravity Complex network Community detection Overlapping nodes 



This work is partially supported by Liaoning Natural Science Foundation under Grant No. 20170540320, the Doctoral Scientific Research Foundation of Liaoning Province under Grant No. 20170520358, the National Natural Science Foundation of China under Grant No. 61473073, the Fundamental Research Funds for the Central Universities under Grant No. N161702001, No. N172410005-2.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Xinyu Huang
    • 1
  • Dongming Chen
    • 1
    Email author
  • Tao Ren
    • 1
  • Dongqi Wang
    • 1
  1. 1.Software CollegeNortheastern UniversityShenyangChina

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