[1] Barabási A-L. The origin of bursts and heavy tails in human dynamics[J]. Nature 2005, 435: 207-211.
[2] 汪秉宏,周涛,周昌松.人类行为、复杂网络及信息挖掘的统计物理研究[J].上海理工大学学报,2012,34(2): 103-117.
Wang B H, Zhou T, Zhou C S. Statistical physics research for human behaviors, complex network and information mining. J. University of Shanghai for Science and Technology, 2012, 34(2): 103-117.
[3] Huang Z, Zeng D, Chen H. Analyzing consumer-product graphs: Empirical findings and applications in recommender systems[J]. Management Science, 2007, 53: 1146-1164.
[4] Latapy M, Magnien C, Vecchio N D. Basic notions for the analysis of large two-mode networks[J]. Social Networks, 2008, 30: 31-48.
[5] Guillaume J-L, Latapy M. Bipartite structure of all complex networks[J]. Inform Process Lett, 2004, 90: 215-221.
[6] Wang C, Ye M. From user comments to on-line conversations[C]. Proceedings of the 18th ACM SIGKDD International Conference on Know ledge Discovery and Data Mining, ACM New York, USA, 2012:244-252.
[7] Ye M, Zhao C, Aperjis C, et al. Collective attention and the dynamics of group deals[C]. Proceedings of the 21st International Conference Companion on World Wide Web, ACM New York, USA,2012:1205-1212.
[8] Liu J G, Hou L, Zhang Y L, et al. Empirical analysis of the clustering coefficient in the user-object bipartite networks[J]. Int J Mod Phys C, 2013, 24(8): 1350055.
[9] Ni J, Zhang Y L, Hu Z L, et al. Ceiling effect of online user interests for the movies[J]. Physica A, 2014, 402: 134-140.
[10] Liu J G, Hu Z L, Guo Q, et al. Effect of the social influence on topological properties of user-object bipartite networks[J]. European Physical Journal B, 2013, 86(11): 478.
[11] Dunbar R I M. Instant expert: evolution of social networks[J]. New Scientist, 2012, 214: 1-8.
[12] Gonc,alves B, Perra N, Vespignani A. Modeling users′ activity on twitter networks: validation of dunbar′s number[J]. PLoS ONE, 2011, 6(8): e22656.
[13] Zhang Z Q, Xie W J, Li M X, Calling patterns in human communication dynamics[J]. Proc Natl Acad Sci USA, 2013, 110(5): 1600-1605.
[14] Guo Q, Shao F, Hu Z L, et al. Statistical properties of the personal social network in the Facebook[J]. EPL, 2013, 104(2): 28004.
[15] Yang G Y, Liu J G. A local-world hypernetwork evolution model[J]. Chinese Physics B, 2013, 23(1): 018901.
[16] Liu J G, Yang G Y, Hu Z L. A knowledge generation model via the hypernetwork[J]. PLoS ONE, 2014, 9(3): e89746.
[17] 刘建国,任卓明,郭强,等.复杂网络节点重要性排序的研究进展. 物理学报, 2013, 62(17): 178901.
Liu Jianguo, Ren Zhuoming, Guo Qiang, et al. Node importance ranking of complex networks[J]. Acta Physica Sinica, 2013, 62(17): 178901.
[18] 刘宏鲲,周涛.中国城市航空网络的实证研究与分析[J].物理学报, 2007, 56: 106-112.
Liu Hongkun, Zhou Tao. Empirical study of Chinese city airline network[J]. Acta Physica Sinica, 2007, 56: 106-112.
[19] Wu J, Barahona M, Tan Y, et al. Robustness of random graphs based on natural connectivity[C]. The Second International Conference on Performance, Safety and Robustness in Complex Systems and Applications, Pesaro, 2012.
[20] Holme P, Kim B J, Yoon C N, et al. Attack vulnerability of complex networks[J]. Phys Rev E, 2002, 65: 056109.
[21] Lü L, Zhang Y C, Yeung C H, et al. Leaders in social networks, the delicious case[J]. PLoS ONE, 2011, 6(6): e21202.
[22] Kitsak M, Gallos L K, Havlin S, et al. Identification of influential spreaders in complex networks[J]. Nat Phys, 2010, 6:888-893.
[23] Chen D. B, Lü L, Shang M S. Identifying influential nodes in complex networks[J]. Physica A, 2011, 391: 1777-1787.
[24] Centola D. The spread of behavior in an online social network[J]. Science, 2010, 329: 1194-1197.
[25] Ugander J, Backstrom L, Marlow C. Structural diversity in social contagion[J]. Proc Natl Acad Sci USA, 2012, 109: 5962-5966.
[26] Zhou Y, Lei T, Zhou T. A robust ranking algorithm to spamming[J]. EPL, 2011, 94: 48002.
[27] Golbeck J. Weaving a web of trust[J]. Science, 2008, 321: 1640.
[28] Kitsak M, Gallos L K, Havlin S, et al. Identification of influential spreaders in complex networks[J]. Nat Phys, 2010, 6(11): 888-893.
[29] Zeng A, Zhang C J. Ranking spreaders by decomposing complex networks[J]. Phys Lett A, 2013, 377: 1031-1035.
[30] Liu J G, Ren Z M, Guo Q. Ranking the spreading influence in complex networks[J]. Physica A, 2013, 392(18): 4154-4159.
[31] Ren Z M, Zeng A, Chen D B, et al. Iterative resource allocation for ranking spreaders in complex networks[J]. EPL, 2014, 106: 48005.
[32] Lü L, Chen D B, Zhou T. The small world yields the most effective information spreading[J]. New J Phys, 2011, 13: 123005.
[33] Sahneh F D, Chowdhury F N, Scoglio C M, et al. On the existence of a threshold for preventive behavioral responses to suppress epidemic spreading[J]. Sci Rep, 2012, 2(6): 632.
[34] Hu Z L, Liu J G, Yang G Y, et al. Effects of the distance among multiple spreaders on the spreading[J]. EPL, 2014, 106: 18002.
[35] Liu J G, Shi K, Guo Q. Solving the accuracy-diversity dilemma via directed random walks[J]. Phys Rev E, 2012, 85: 016118.
[36] Liu J G, Zhou T, Guo Q. Information filtering via biased heat conduction[J]. Phys Rev E, 2011, 84(3): 037101.
[37] Zhou T, Kuscsik Z, Liu J G, et al. Solving the apparent diversity-accuracy dilemma of recommender systems[J]. Proc Natl Acad Sci USA, 2010, 107(10): 4511-4515.
[38] Liu J, Zhou T, Wang B H, et al. Effect of user tastes on personalized recommendation[J]. Int J Mod Phys C, 2009 20: 1925-1932.
[39] Anna Nagurney.超网络:复杂性科学[J].上海理工大学学报,2011,33(3): 205-228.
Anna Nagurney. Supernetwork: the science of complexity[J]. J University of Shanghai for Science and Technology, 2011, 33(3): 205-228.
