A modified efficiency centrality to identify influential nodes in weighted networks

被引：34
|
作者：
Wang, Yunchuan [1 ]
Wang, Shasha [2 ]
Deng, Yong [3 ,4 ,5 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Elect Sci & Engn, Chengdu, Sichuan, Peoples R China
[2] Sichuan Univ, Sch Comp Sci, Chengdu, Sichuan, Peoples R China
[3] Univ Elect Sci & Technol China, Inst Fundamental & Frontier Sci, Chengdu, Sichuan, Peoples R China
[4] Jinan Univ, Big Data Decis Inst, Guangzhou, Guangdong, Peoples R China
[5] Southwest Univ, Sch Comp & Informat Sci, Chongqing, Peoples R China
来源：
PRAMANA-JOURNAL OF PHYSICS | 2019年 / 92卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Complex network; influential nodes; weighted network; efficiency centrality; COMPLEX NETWORKS; LARGE-SCALE; DYNAMICS; SYNCHRONIZATION; IDENTIFICATION;
D O I：
10.1007/s12043-019-1727-1
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
It is still a crucial issue to identify influential nodes effectively in the study of complex networks. As for the existing efficiency centrality (EffC), it cannot be applied to a weighted network. In this paper, a modified efficiency centrality (EffC) is proposed by extending EffC into weighted networks. The proposed measure trades off the node degree and global structure in a weighted network. The influence of both the sum of the average degree of nodes in the whole network and the average distance of the network is taken into account. Numerical examples are used to illustrate the efficiency of the proposed method.
引用
收藏
页数：11
相关论文
共 50 条
  • [31] Identifying Influential Nodes in Complex Networks Based on Weighted Formal Concept Analysis
    Sun, Zejun
    Wang, Bin
    Sheng, Jinfang
    Hu, Yixiang
    Wang, Yihan
    Shao, Junming
    IEEE ACCESS, 2017, 5 : 3777 - 3789
  • [32] SLGC: Identifying influential nodes in complex networks from the perspectives of self-centrality, local centrality, and global centrality
    Ai, Da
    Liu, Xin-Long
    Kang, Wen-Zhe
    Li, Lin-Na
    Lu, Shao-Qing
    Liu, Ying
    CHINESE PHYSICS B, 2023, 32 (11)
  • [33] Identifying influential nodes in complex networks based on a spreading influence related centrality
    Chen, Xing
    Tan, Mian
    Zhao, Jing
    Yang, Tinghong
    Wu, Duzhi
    Zhao, Rulan
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2019, 536
  • [34] A new Centrality Measure for Identifying Influential Nodes in Social Networks
    Rhouma, Delel
    Ben Romdhane, Lotfi
    TENTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2017), 2018, 10696
  • [35] Normalized strength-degree centrality: identifying influential spreaders for weighted network
    Sadhu, Srestha
    Namtirtha, Amrita
    Malta, Mariana Curado
    Dutta, Animesh
    SOCIAL NETWORK ANALYSIS AND MINING, 2024, 14 (01)
  • [36] A novel measure to identify influential nodes: Return Random Walk Gravity Centrality
    Curado, Manuel
    Tortosa, Leandro
    Vicent, Jose F.
    INFORMATION SCIENCES, 2023, 628 : 177 - 195
  • [37] A Novel Entropy-Based Centrality Approach for Identifying Vital Nodes in Weighted Networks
    Qiao, Tong
    Shan, Wei
    Yu, Ganjun
    Liu, Chen
    ENTROPY, 2018, 20 (04)
  • [38] A method based on k-shell decomposition to identify influential nodes in complex networks
    HamaKarim, Bakhtyar Rafeeq
    Mohammadiani, Rojiar Pir
    Sheikhahmadi, Amir
    Hamakarim, Bryar Rafiq
    Bahrami, Mehri
    JOURNAL OF SUPERCOMPUTING, 2023, 79 (14) : 15597 - 15622
  • [39] The random walk-based gravity model to identify influential nodes in complex networks
    Zhao, Jie
    Wen, Tao
    Jahanshahi, Hadi
    Cheong, Kang Hao
    INFORMATION SCIENCES, 2022, 609 : 1706 - 1720
  • [40] Mining Influential Nodes in Urban Road Networks Based on Semi-local Centrality
    Liu Weiyan
    Liu Bin
    Liu Tao
    2018 10TH INTERNATIONAL CONFERENCE ON COMMUNICATIONS, CIRCUITS AND SYSTEMS (ICCCAS 2018), 2018, : 222 - 226
12345