Abstract
As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. Traditional on-line social network researches are based a certain comment interaction. Though some interest conclusions have been obtained, the understanding of the entire on-line social network is one-sided. In this paper, we compare four different types of networks proposed by previous researchers. Statistical analysis reveals that those four networks are consistent in nature (both the “small-world effect” and skewed degree distributions are found in them). To discover the mechanism behind these network observations, we propose a single-factor model with a single parameter K; using this model, various networks can be obtained when we change the parameter K in a given range. Simulation experiment based on this model show that the simulation results and the real data are consistent, which means that our model is valid.
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References
Goh, K.-I., Eom, Y.-H., Jeong, H., Kahng, B., Kim, D.: Structure and evolution of online social relationships: Heterogeneity in unrestricted discussions. Phys. Rev. E 73, 066123 (2006)
Gomez, V., Kaltenbrunner, A., Lopez, V.: Statistical analysis of the social network and discussion threads in slashdot. In: WWW, Beijing, China, April 21-25 (2008)
Chen, I.-X., Yang, C.-Z.: Visualization of Social Networks. In: Handbook of Social Network Technologies and Applications, Part 5, pp. 585–610 (2010)
Kou, Z., Zhang, C.: Reply networks on a bulletin board system. Phys. Rev. E 67, 036117 (2003)
Mishne, G., Glance, N.: Leave a reply: an analysis of weblog comments. In: WWW, May 22-26 (2006)
Yano, T., Smith, N.A.: What’s worthy of comment? Content and comment volume in political blogs. In: 4th Int’l AAAI Conference on Weblogs and Social Media (2010)
Watts, D.J.: Small Worlds. Princeton University Press, Princeton (1999)
Newman, M.E.J.: Assortative mixing in networks. Phys. Rev. Lett. 89, 208701 (2087)
Bo, R., Xia, Z., Yongzhen, Z., Bu, Z.: Research on BBS Complex Online Network and Members Interactive Characteristics (2009) (Chinese version)
Soffer, S.N., Vazquez, A.: Network clustering coefficient without degree-correlation biases. Phys. Rev. E 71, 051701 (2005)
Goldberg, M., Kelley, S., Magdon-Ismail, M., Mertsalov, K., Wallace, W.A.: Communication Dynamics of Blog Networks. In: Giles, L., Smith, M., Yen, J., Zhang, H. (eds.) SNAKDD 2008. LNCS, vol. 5498, pp. 36–54. Springer, Heidelberg (2010)
Newman, M.E.J.: Mixing patterns in networks. Phys. Rev. E 67, 026126 (2003)
Rangwala, H., Jamali, S.: Defining a Coparticipation Network Using Comments on Digg. In: Association for the Advancement of Artificial Intelligence (2010)
Boguna, M., Pastor-Satorras, R.: Epidemic spreading in correlated complex networks. Phys. Rev. E 66, 047104 (2002)
Boguna, M., Pastor-Satorras, R., Vespignani, A.: Absence of epidemic threshold in scale-free networks with degree correlations. Lect. Notes Phys. 625, 127 (2003)
Xia, Z.Y.: Fighting criminals: Adaptive inferring and choosing the next investigative objects in the criminal network. Knowledge-Based Systems (2008)
Xia, Z., Wang, J.: DIMH: A novel model to detect and isolate malicious hosts for mobile ad hoc network. Computer Standards & Interfaces, 660–669 (2006)
Xia, Z.: A Novel Policy and Information Flow Security Model for Active Network. In: Chen, H., Moore, R., Zeng, D.D., Leavitt, J. (eds.) ISI 2004. LNCS, vol. 3073, pp. 42–55. Springer, Heidelberg (2004)
Luo, X., Xu, Z., Yu, J., Chen, X.: Building Association Link Network for Semantic Link on WebResources. IEEE Transactions on Automation Scienceand Engineering (forthcoming)
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Zhan, B., Xia, Z. (2011). A Link Analysis Model Based on Online Social Networks. In: Gong, Z., Luo, X., Chen, J., Lei, J., Wang, F.L. (eds) Web Information Systems and Mining. WISM 2011. Lecture Notes in Computer Science, vol 6988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23982-3_39
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DOI: https://doi.org/10.1007/978-3-642-23982-3_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23981-6
Online ISBN: 978-3-642-23982-3
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