A new centrality measure based on the negative and positive effects of clustering coefficient for identifying influential spreaders in complex networks-Reference-Cited by-同舟云学术

A new centrality measure based on the negative and positive effects of clustering coefficient for identifying influential spreaders in complex networks

Published:2018-05 Issue: Volume:110 Page:41-54
ISSN:0960-0779
Container-title:Chaos, Solitons & Fractals
language:en
Short-container-title:Chaos, Solitons & Fractals

Author:

Berahmand Kamal^ORCID,Bouyer Asgarali^ORCID,Samadi Negin

Publisher

Elsevier BV

Subject

General Mathematics,General Physics and Astronomy,Statistical and Nonlinear Physics,Applied Mathematics

Reference49 articles.

1. Challenges in network science: applications to infrastructures, climate, social systems and economics;Havlin;Eur Phys J Spec Top,2012

2. Improved method of node importance evaluation based on node contraction in complex networks;Jia-sheng;Procedia Eng,2011

3. Vital nodes identification in complex networks;Lü;Phys Rep,2016

4. Exploring complex networks;Strogatz;Nature,2001

5. The structure and function of complex networks;Newman;SIAM Rev,2003

Cited by 83 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel ranking approach for identifying crucial spreaders in complex networks based on Tanimoto Correlation;Expert Systems with Applications;2024-12

2. Identifying influential spreaders in complex networks based on local and global structure;Journal of Computational Science;2024-10

3. Towards investigating influencers in complex social networks using electric potential concept from a centrality perspective;Information Fusion;2024-09

4. Measuring the centrality of nodes in networks based on the interstellar model;Information Sciences;2024-09

5. Multiple criteria decision modeling in social networks: An application to identify opinion leaders in online public opinion events;Expert Systems with Applications;2024-09