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| User′s Behavior Analysis of Online Social Systems |
| GUO Qiang, LIU Jianguo
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| Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, China |
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Abstract In this paper, we present the advanced progress of the online social interaction, rating behaviors, hypergraph model construction, node importance identification and the information diffusion of online social systems, as well as the possible future directions, which could shed some light on the corresponding progress.
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Received: 25 September 2014
Published: 22 June 2026
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[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. |
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