Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 210800177-5.doi: 10.11896/jsjkx.210800177

• Big Data & Data Science • Previous Articles     Next Articles

Ranking and Recognition of Influential Nodes Based on k-shell Entropy

YUAN Hui-lin1, FENG Chong2   

  1. 1 College of Management,Northeastern University,Qinhuangdao,Hebei 066004,China
    2 College of Information Science and Engineering,Northeastern University,Shenyang 110819,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:YUAN Hui-lin,born in 1969,Ph.D,professor.Her main research interests include modeling and optimization of complex systems,information retrieval and artificial intelligence.
    FENG Chong,born in 1997,postgra-duate.His main research interests include complex network and artificial intelligence.
  • Supported by:
    Northeastern University Industry-University-Research Strategic Cooperation Project(71971050),Northeastern University Qinhuangdao Branch Yonghui-Supermarket Industry-University-Research Cooperation Strategic Framework Agreement(7043902891801).

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Abstract: The spreading capacity of nodes has been one of the most attractive problems in the field of complex networks.Due to the large size of nodes in network,researchers want to find accurate measures to estimate the spreading capacity of nodes.In this paper,a new method is proposed based on the basic concepts of information theory and k-shell,which measures the spreading capacity of nodes according to the topological information of their locations in the network.Experimental results show that the proposed method is more effective than other similar methods,and can effectively avoid the “rich club phenomenon” of k-shell method.

Key words: Complex network, Influential node, k-shell entropy, Information spreading

CLC Number: 

  • TP311
[1]ZHAO Y,LI S,JIN F.Identification of influential nodes in social networks with community structure based on label propagation [J].Neurocomputing,2016,210:34-44.
[2]FREEMAN L C.Centrality in social networks conceptual clarification [J].Social Networks,1978,1(3):215-239.
[3]SABIDUSSI G.The centrality index of a graph[J].Psy-chometrika,1966,31(4):581-603.
[4]FREEMAN L C.A Set of Measures of Centrality Based on Betweenness[J].Sociometry,1977,40(1):35-41.
[5]BAE J,KIM S.Identifying and ranking influential spreaders in complex networks by neighborhood coreness[J].Physica A:Statistical Mechanics and its Applications,2014,395(4):549-559.
[6]WANG J,HOU X,LI K.A novel weight neighborhood centra-lity algorithm for identifying influential spreaders in complex networks[J].Physica A:Statistical Mechanics and its Applications,2017,475:88-105.
[7]HAJARATHAIAH K,ENDURI M K,ANAMALAMUDI S.Efficient algorithm for finding the influential nodes using local relative change of average shortest path[J].Physica A:Statistical Mechanics and Its Applications,2022,591:126708.
[8]LIU J G,WANG Z Y,GUO Q.Identifying multiple influential spreaders via local structural similarity[J].Europhysics Letters,2017,119(1):18001.
[9]KITSAK M,GALLOS L K,HAVLIN S.Identification of influen-tial spreaders in complex networks[J].Nature Physics,2010,6(11):888-893.
[10]REN Z M,LIU J G L,SHAO F.Analysis of the spreading influence of the nodes with minimum K-shell value in complex networks[J].Acta Physica Sinica,2013,62(10):956-959.
[11]HU Z L,LIU J G,YANG G Y.Effects of the distance among multiple spreaders on the spreading[J].Europhysics Letters,2014,106(1):18002.
[12]GUO L,LIN J H,GUO Q.Identifying multiple influentialspreaders in term of the distance-based coloring[J].Physics Letters A,2016,380(7/8):837-842.
[13]ZHANG J X,CHEN D B,DONG Q.Identifying a set of influential spreaders in complex networks[J].Scientific Reports,2016,6:27823.
[14]BIAN T,DENG Y.Identifying influential nodes in complex networks:A node information dimension approach[J].Chaos:An Interdisciplinary Journal of Nonlinear Science,2018,28(4):043109.
[15]WANG Z,ZHAO Y,XI J,et al.Fast ranking influential nodes in complex networks using a k-shell iteration factor[J].Physica A: Statistical Mechanics and its Applications,2016,461:171-181.
[16]ZAREIE A,SHEIKHAHMADI A,JALILI M.Influential node ranking in social networks based on neighborhood diversity[J].Future Generation Computer Systems,2019,94:120-129.
[17]LIU Y,WEI B,DU Y.Identifying influential spreaders byweight degree centrality in complex networks[J].Chaos,Solitons & Fractals,2016,86:1-7.
[18]ZENG A,ZHANG C J.Ranking spreaders by decomposing com-plex networks[J].Physics Letters A,2013,377(14):1031-1035.
[19]LIU J G,REN Z M,GUO Q.Ranking the spreading influence in complex networks[J].Physica A:Statistical Mechanics and its Applications,2013,392(18):4154-4159.
[20]SHEIKHAHMADI A,NEMATBAKHSH M A.Identification of multi-spreader users in social networks for viral marketing[J].Journal of Information Science,2017,43(3):412-423.
[21]CARMI S,HAVLIN S,KIRKPATRICK S,et al.A model of Internet topology using k-shell decomposition[J].Proceedings of the National Academy of Sciences,2007,104(27):11150-11154.
[22]LUSSEAU D,SCHNEIDER K,BOISSEAU O J.The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations[J].Behavioral Ecology and Sociobiology,2003,54(4):396-405.
[23]GLEISER P M,DANON L.Community structure in jazz[J].Advances in Complex Systems,2003,6(4):565-573.
[24]NEWMAN M E J.Finding community structure in networksusing the eigenvectors of matrices[J].Physical Review E,2006,74(3):036104.
[25]RABADE R,MISHRA N,SHARMA S.Survey of influentialuser identification techniques in online social networks[M]//Recent Advances in Intelligent Informatics.Cham:Springer,2014:359-370.
[26]GIRVAN M,NEWMAN M E J.Community structure in social and biological networks[J].Proceedings of the National Academy of Sciences,2002,99(12):7821-7826.
[27]MEHLHORN K,NÄHER S,UHRIG C.The LEDA platformfor combinatorial and geometric computing[C]//International Colloquium on Automata,Languages,and Programming.Berlin:Springer,1997:7-16.
[28]SOUAM F,AÏTELHADJ A,BABA-ALI R.Dual modularityoptimization for detecting overlapping communities in bipartite networks[J].Knowledge and Information Systems,2014,40(2):455-488.
[29]COLIZZA V,PASTOR-SATORRAS R,VESPIGNANI A.Reaction-diffusion processes and metapopulation models in heterogeneous networks[J].Nature Physics,2007,3(4):276-282.
[30]WHITE J G,SOUTHGATE E,THOMSON J N,et al.Thestructure of the nervous system of the nematode Caenorhabditis elegans[J].Philos Trans R Soc Lond B Biol Sci,1986,314(1165):1-340.
[31]WEN T,JIANG W.Identifying influential nodes based on fuzzy local dimension in complex networks[J].Chaos,Solitons & Fractals,2019,119:332-342.
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