Tao Yu, Zhao-Wen Zhang, Wen-Bin Zhao, Tong-Rang Fan, and Jilong Wang


  1. [1] D. Gruhl, R. Guha, D. Liben-Nowell, et al., Information diffusion through blogspace, Proceedings of the 13th InternationalConference on World Wide Web. ACM, 2004, 491–501.
  2. [2] D. Liginlal and L. Khansa, Information contagion: An empiricalstudy of the spread of news on Digg and Twitter social networks,Eprint Arxiv, 52, 2010,166–176.
  3. [3] S. Yan, S. Tang, S. Pei, et al., The spreading of oppositeopinions on online social networks with authoritative nodes,Physica A: Statistical Mechanics and its Applications, 392(17),2013, 3846–3855.
  4. [4] Z.-Q. Zhu, C.-J. Liu, J.-L. Wu, J. Xu, and B. Liu, The influenceof human heterogeneity to information spreading, Journal ofStatistical Physics, 154(6), 2014, 1569–1577.
  5. [5] P. Cui, M. Tang, and Z.X. Wu, Message spreading in networkswith stickiness and persistence: Large clustering does notalways facilitate large-scale diffusion, Scientific Reports, 4,2014.
  6. [6] P. Shu, Effects of memory on information spreading in complexnetworks, Computational Science and Engineering (CSE), 2014IEEE 17th International Conf. on. Computational Science andEngineering, Chengdu, China, 2015, 554–556.
  7. [7] Y. Zhang and J. Xu, A rumor spreading model considering thecumulative effects of memory, Discrete Dynamics in Natureand Society, 2015, 2015(204395), 1–11.
  8. [8] S. Staab, P. Domingos, P. Mike, et al., Social networks applied,IEEE Intelligent Systems, 20(1), 2005, 80–93.
  9. [9] I. Kanovsky and O. Yaari, Viral opinion spreading model insocial networks, Social Computing (SocialCom), 2013 Inter-national Conf. on. IEEE, 2013, 971–974.
  10. [10] J. Huang, C. Li, W.Q. Wang, et al., Temporal scaling ininformation propagation, Scientific Reports, 2014, 4(5334),1–6.
  11. [11] Z.J. Zhang, G.Q. Mao, B.D.O. Anderson, On the informa-tion propagation in mobile ad-hoc networks using epidemicrouting, Proc. of the 54th Annual IEEE Global Telecommunica-tions Conf.: “Energizing Global Communications , GLOBE-COM 2011, New York, Institute of Electrical and ElectronicsEngineers Inc., 2011.
  12. [12] J. Waters and M.G. Ceruti, Modeling and simulation of in-formation flow: A study of info dynamic quantities, Proc. ofthe 15th International Command and Control Research andTechnology Symposium, San Diego, Space and Naval WarfareSystems Center Pacific San Diego Ca, 2010, 117–131.
  13. [13] C.N. Lin, K.L. Hsieh, J. Roan, et al., The application ofstructural holes theory to supply chain network informationflow analysis, Information Technology Journal, 10(1), 2011,146–151.
  14. [14] G. Briscoe and A. Marinos, Digital ecosystems in the clouds:Towards community cloud computing, IEEE Digital Ecosys-tems and Technologies, 12(7), 2009, 103–108.
  15. [15] H. Zhijie, H. Liusheng, W. Ruchuan, et al., A location-basedrouting algorithm combined with the topology control forwireless sensor network, Journal of Computer Research andDevelopment, 47(z2), 2010, 128–132.
  16. [16] R. K. Pon, A.F. Cardenas, D. J. Buttler, et al., Measuringthe interestingness of articles in a limited user environment,Information Processing & Management, 47(1), 2011, 97–116.
  17. [17] Q. Li, J. Wang, Y.P. Chen, et al., User comments for newsrecommendation in forum-based social media, InformationSciences, 180(24), 2010, 4929–4939.
  18. [18] D. Lu and Q. Li, Exploiting semantic hierarchies for Flickrgroup, Active Media Technology, 6335, 2010, 74–85.
  19. [19] R.A. Negoescu and D. Gatica Perez, Modeling Flickr commu-nities through probabilistic topic-based analysis, IEEE Trans-actions on Multimedia, 12(5), 2010, 399–416.
  20. [20] L. Jian-Guo, R. Zhuo-Ming, G. Qiang, W. Bing-Hong, Nodeimportance ranking of complex networks, Acta Physica Sinica,62(17), 2013, 1–10.
  21. [21] R. Zhuo-Ming, S. Feng, L. Jian-Guo, et al., Node importancemeasurement based on the degree and clustering coefficientinformation, Acta Physica Sinica, 62(12), 2013, 1–5.
  22. [22] R. Poulin, M.C. Boily, and B.R. Masse, Dynamical systemsto define centrality in social networks, Social Networks, 22(3),2000, 187–220.
  23. [23] G. Sabidussi, The centrality index of a graph, Psychometrika,31(4), 1966, 581–603.
  24. [24] J. Zhang, X.K. Xu, P. Li, et al., Node importance for dynamicalprocess on networks: A multiscale characterization, Chaos: AnInterdisciplinary Journal of Nonlinear Science, 21(1), 2011,016107.
  25. [25] L.C. Freeman, A set of measures of centrality based on be-tweenness, Sociometry, 40(1), 1977, 35–41.
  26. [26] Z. Wenbin and Z. Zhengxu, Research on engineering softwaredata formats conversion network, Journal of Software, 7(11),2012, 2606–2613.
  27. [27] L. Lu, J. Geng, Q. Gao, Industrial clusters trading networkbased on heterogeneity, Complex Systems and ComplexityScience, 11(2), 2014, 44–51.
  28. [28] J. Yang, J. Zeng, and J. Zhang, Structural heterogeneity ofopen-source software communities based on complex networks,Journal of South China University of Technology, 41(12), 2013,136–144.
  29. [29] M.A. Aydin, A.H. Zaim, and K.G. Ceylan, A hybrid intru-sion detection system design for computer network security,Computers and Electrical Engineering, 35, 2009, 517–526.

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