@article{89489f770f2749988344a2abdc32c2df,
title = "Identifying influential nodes in weighted networks based on evidence theory",
abstract = "The design of an effective ranking method to identify influential nodes is an important problem in the study of complex networks. In this paper, a new centrality measure is proposed based on the Dempster-Shafer evidence theory. The proposed measure trades off between the degree and strength of every node in a weighted network. The influences of both the degree and the strength of each node are represented by basic probability assignment (BPA). The proposed centrality measure is determined by the combination of these BPAs. Numerical examples are used to illustrate the effectiveness of the proposed method.",
keywords = "Complex networks, Dempster-Shafer theory of evidence, Influential nodes, Weighted network",
author = "Daijun Wei and Xinyang Deng and Xiaoge Zhang and Yong Deng and Sankaran Mahadevan",
note = "Funding Information: We greatly appreciate the editor{\textquoteright}s encouragement and the anonymous reviewer{\textquoteright}s valuable comments and suggestions to improve this work. The Ph.D candidates of the corresponding author in Shanghai Jiao Tong University, Xiaoyan Su and Peida Xu, provided valuable discussions on the algorithm in this paper. The work is partially supported by Chongqing Natural Science Foundation (for Distinguished Young Scholars), Grant No. CSCT, 2010BA2003 , National Natural Science Foundation of China , Grant Nos. 60933006 and 61174022 , National High Technology Research and Development Program of China (863 Program) (No. 2013AA013801 ), the Fundamental Research Funds for the Central Universities , Grant No. XDJK2012D009 , Doctor Funding of Southwest University Grant No. SWU110021 , China State Key Laboratory of Virtual Reality Technology and Systems .",
year = "2013",
month = may,
day = "15",
doi = "10.1016/j.physa.2013.01.054",
language = "English",
volume = "392",
pages = "2564--2575",
journal = "Physica A: Statistical Mechanics and its Applications",
issn = "0378-4371",
publisher = "Elsevier B.V.",
number = "10",
}