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Chin. Phys. B, 2020, Vol. 29(8): 088903    DOI: 10.1088/1674-1056/ab969f
INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY Prev   Next  

Influential nodes identification in complex networks based on global and local information

Yuan-Zhi Yang(杨远志)1, Min Hu(胡敏)2, Tai-Yu Huang(黄泰愚)3
1 Air Force Engineering University, Xi'an 710038, China;
2 China Petroleum Planning and Engineering Institute, Beijing 100083, China;
3 Sichuan University of Arts and Science, Dazhou 635000, China
Abstract  Identifying influential nodes in complex networks is essential for network robust and stability, such as viral marketing and information control. Various methods have been proposed to define the influence of nodes. In this paper, we comprehensively consider the global position and local structure to identify influential nodes. The number of iterations in the process of k-shell decomposition is taken into consideration, and the improved k-shell decomposition is then put forward. The improved k-shell decomposition and degree of target node are taken as the benchmark centrality, in addition, as is well known, the effect between node pairs is inversely proportional to the shortest path length between two nodes, and then we also consider the effect of neighbors on target node. To evaluate the performance of the proposed method, susceptible-infected (SI) model is adopted to simulate the spreading process in four real networks, and the experimental results show that the proposed method has obvious advantages over classical centrality measures in identifying influential nodes.
Keywords:  complex networks      influential nodes      global position      local structure      susceptible-infected (SI) model  
Received:  23 April 2020      Revised:  18 May 2020      Published:  05 August 2020
PACS:  89.75.Fb (Structures and organization in complex systems)  
Corresponding Authors:  Min Hu, Min Hu     E-mail:  hu_min_min@163.com;1097762865@qq.com

Cite this article: 

Yuan-Zhi Yang(杨远志), Min Hu(胡敏), Tai-Yu Huang(黄泰愚) Influential nodes identification in complex networks based on global and local information 2020 Chin. Phys. B 29 088903

[1] Shao P and Chen H 2019 IEEE Access 7 118509
[2] Arularasan A N, Suresh A and Seerangan K 2019 Cluster Computing 22 4035
[3] Shukla A, Bhattacharyya A, Kuppusamy L, Srivas M and Thattai M 2017 Plos One 12 e0180692
[4] Mou J, Liu C, Chen S, Huang G and Lu X 2017 Sci. Rep. 7 1275
[5] Tan Z Z, Asad J H and Owaidat M Q 2017 Int. J. Circuit Theor. Appl. 45 1942
[6] Owaidat M Q, Al-Badawi A A, Asad J H and Al-Twiessi Mohammed 2018 Chin. Phys. Lett. 35 020502
[7] Chasman D, Siahpirani A F and Roy S 2016 Current Opinion in Biotechnology 39 157
[8] Yuan M, Hong W and Li P 2017 Biochemical Society Transactions 45 1015
[9] Bonacich P 1972 Journal of Mathematical Sociology 2 113
[10] Freeman L C 1978 Social Networks 1 215
[11] Newman M E J 2005 Social Networks 27 39
[12] Bonacich P and Lloyd P 2001 Social Networks 23 191
[13] Chen D, Lü L, Shang M S, Zhang Y C and Zhou T 2012 Physica A 391 1777
[14] Kistak M, Gallos L K, Havlin S, Liljeros F, Muchnik L, Stanley H E and Makse H A 2010 Nat. Phys. 6 888
[15] Zeng A and Zhang C J 2013 Phys. Lett. A 377 1031
[16] Lin J H, Guo Q, Dong W Z, Tang L Y and Liu J G 2014 Phys. Lett. A 378 3279
[17] Arasu A, Cho J, Garcia-Molina H, Paepcke A and Raghavan S 2001 ACM Transactions on Internet Technology 1 2
[18] Lü L, Zhang Y C, Yeung C H and Zhou T 2011 Plos One 6 e21202
[19] Kleinberg J M 1999 J. ACM 46 604
[20] Liu Z, Jiang C, Wang J and Yu H 2015 Knowledge-Based Systems 84 56
[21] Yang Y, Yu L, Wang X, Zhou Z, Chen Y and Kou T 2019 Physica A 526 121118
[22] Mo H, Gao C and Deng Y 2015 Journal of Systems Engineering and Electronics 26 381
[23] Ibnoulouafi A, Haziti M E and Cherifi H 2018 Journal of Statistical Mechanics Theory and Experiment 7 073407
[24] Wang Z, Du C, Fan J and Xing Y 2017 Neurocomputing 260 466
[25] Zhao X, Liu F, Wang J and Li T 2017 International Journal of Geo-Information 6 35
[26] Zhou T, Liu J G, Bai W J, Chen G and Wang B H 2006 Phys. Rev. E 74 056109
[27] Zachary W W 1977 Journal of Anthropological Research 33 452
[28] Gleiser P M and Danon L 2003 Advances in Complex Systems 6 565
[29] Guimerá R, Danon L, Díaz-Guilera A, Giralt F and Arenas A 2003 Phys. Rev. E 68 065103
[30] Kendall M G 1938 Biometrika 30 81
[31] Bae J and Kim S 2014 Physica A 395 549
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