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Chin. Phys. B, 2015, Vol. 24(10): 100101    DOI: 10.1088/1674-1056/24/10/100101
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Rapid identifying high-influence nodes in complex networks

Song Boa, Jiang Guo-Pingb, Song Yu-Rongb, Xia Ling-Linga
a School of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
b School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
Abstract  A tiny fraction of influential individuals play a critical role in the dynamics on complex systems. Identifying the influential nodes in complex networks has theoretical and practical significance. Considering the uncertainties of network scale and topology, and the timeliness of dynamic behaviors in real networks, we propose a rapid identifying method (RIM) to find the fraction of high-influential nodes. Instead of ranking all nodes, our method only aims at ranking a small number of nodes in network. We set the high-influential nodes as initial spreaders, and evaluate the performance of RIM by the susceptible-infected-recovered (SIR) model. The simulations show that in different networks, RIM performs well on rapid identifying high-influential nodes, which is verified by typical ranking methods, such as degree, closeness, betweenness, and eigenvector centrality methods.
Keywords:  high-influence nodes      dynamic model      complex networks      centrality measures     
Received:  11 February 2015      Published:  05 October 2015
PACS:  01.75.+m (Science and society)  
  89.70.Eg (Computational complexity)  
  89.75.Fb (Structures and organization in complex systems)  
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61374180 and 61373136), the Ministry of Education Research in the Humanities and Social Sciences Planning Fund Project, China (Grant No. 12YJAZH120), and the Six Projects Sponsoring Talent Summits of Jiangsu Province, China (Grant No. RLD201212).
Corresponding Authors:  Jiang Guo-Ping     E-mail:  jianggp@njupt.edu.cn

Cite this article: 

Song Bo, Jiang Guo-Ping, Song Yu-Rong, Xia Ling-Ling Rapid identifying high-influence nodes in complex networks 2015 Chin. Phys. B 24 100101

[1] Wu X D, Li Y and Li L 2014 Chin. J. Comput. 37 735 (in Chinese)
[2] Wang L, Wang J, Shen H W and Cheng X Q 2013 Chin. Phys. B 22 108903
[3] Konstantin K, Ángeles S M and San M M 2012 Sci. Rep. 2 292
[4] Yı ldı rı m M A, Goh K I, Cusick M E, Barabási A L and Vidal M 2007 Nat. Biotechnol. 25 1119
[5] Ren X L and Lü L Y 2014 Chin. Sci. Bull. 59 1175 (in Chinese)
[6] Bonacich P 1972 J. Math. Sociol. 2 113
[7] Kitsak M, Gallos L K, Havlin S, Liljeros F, Muchnik L, Stanley H E and Makse H A 2010 Nat. Phys. 6 888
[8] Freeman L C 1977 Sociometry 40 35
[9] Freeman L C 1979 Social Networks 1 215
[10] Callaway D, Newman M, Strogatz S and Watts D 2000 Phys. Rev. Lett. 85 5468
[11] Brin S and Page L 1998 Computer Networks and ISDN Systems 30 107
[12] Kleinberg J M 1999 JACM 46 604
[13] Li P X, Ren Y Q and Xi Q M 2004 Systems Engineering 22 13 (in Chinese)
[14] Tan Y J, Wu J and Deng H Z 2006 Systems Engineering: Theory & Practice 26 79( in Chinese)
[15] Chen D B, Lü L Y and Shang M S, Zhang Y C and Zhou T 2012 Physica A 391 1777
[16] Lü L, Zhang Y C, Yeung C H and Zhou T 2011 PLoS ONE 6 e21202
[17] Zhao Z Y, Yu H, Zhu Z L and Wang X F 2014 Chin. J. Comput. 37 753 (in Chinese)
[18] Hu Q C, Yin Y S and Ma P F 2013 Acta Phys. Sin. 62 140101 (in Chinese)
[19] Ren Z M, Liu J G, Shao F, Hu Z L and Guo Q 2013 Acta Phys. Sin. 62 108902(in Chinese)
[20] Yang X, Huang D C and Zhang Z K 2015 Acta Phys. Sin. 64 050502(in Chinese)
[21] Su X P and Song Y R 2015 Acta Phys. Sin. 64 020101(in Chinese)
[22] Pei S, Muchnik L, Andrade J S Jr and Zheng Z 2014 Sci. Rep. 4 5547
[23] Iyer S, Killingback T, Sundaram B and Wang Z 2013 PLoS ONE 8 e59613
[24] Gross T, D'Lima C J D and Blasius B 2006 Phys. Rev. Lett. 96 208701
[25] Pastor-Satorras R and Vespignani A 2001 Phys. Rev. Lett. 86 3200
[26] Floyd R W 1962 Commun. ACM 5 345
[27] Johnson and Donald B 1977 J. ACM 24 1
[28] Brandes U 2001 J. Math. Sociol. 25 163
[29] Zachary W W 1977 J. Anthropol. Res. 33 452
[30] Guimerá R, Danon L, Díz-Guilera A, Giralt F and Arenas A 2003 Phys. Rev. E 68 065103
[31] Watts D J and Strogatz S H 1998 Nature 393 440
[32] Newman M E J 2002 Phys. Rev. Lett. 89 208701
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