Abstract
Social network analysis has been a hot topic in the field of graph mining. After people have achieved the goal of detecting communities from various networks, now they are interested in how these explored communities change as time passes by. In other words, people focus on the problem of community evolution and further discover those dynamic characteristics of kinds of networks. Here, we propose CommTracker, a novel and parameter-free algorithm of tracking community evolution, which utilizes the representative quality of core nodes in a community to establish the evolving relationship between two communities in consecutive time snapshots. With such a distinct strategy, it is suitable for analyzing large scale datasets. Depending on relationships established from CommTracker, it is feasible to identify community split and mergence. In addition, one relationship amongst evolution traces, evolution traces intersection, is also studied. At last, we demonstrate the correctness and effectiveness of our algorithm on 4 real datasets.
This work is supported by the National Natural Science Foundation of China under Grant 60402011 and National Eleven Five-Year Scientific and Technical Support Plans under Grant 2006BAH03B05.
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References
Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286, 509 (1999)
Qiao, S., Tang, C., Peng, J., Fan, H., Xiang, Y.: Vccm mining: Mining virtual community core members based on gene expression programming. In: Chen, H., Wang, F.-Y., Yang, C.C., Zeng, D., Chau, M., Chang, K. (eds.) WISI 2006. LNCS, vol. 3917, pp. 133–138. Springer, Heidelberg (2006)
Liu, Q., Tang, C., Qiao, S., Liu, Q., Wen, F.: Mining the core member of terrorist crime group based on social network analysis. In: Yang, C.C., Zeng, D., Chau, M., Chang, K., Yang, Q., Cheng, X., Wang, J., Wang, F.-Y., Chen, H. (eds.) PAISI 2007. LNCS, vol. 4430, pp. 311–313. Springer, Heidelberg (2007)
Du, N., Wu, B., Pei, X., Wang, B., Xu, L.: Community detection in large-scale social networks. In: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis, pp. 16–25 (2007)
Givan, M., Newman, M.: Community structure in social and biological networks. PNAS (2002)
Palla, J., Derényi, I., Farkas, I., Vicsek, T.: Uncovering the overlapping community structure of complex network in nature and society. Nature 435 (2005)
Donetti, L., Munoz, M.: Detecting network communities: a new systematic and efficient algorithm. Journal of Statistical Mechanics 443 (2004)
Hopcroft, J., Khan, O., Kulis, B., Selman, B.: Natural communities in large linked networks. In: Proceedings of ACM SIGKDD, pp. 541–546 (2003)
Guimera, R., Amaral, L.A.N.: Functional cartography of complex metabolic networks. Functional cartography of complex metabolic networks 443 (2005)
Wu, B., Pei, X., Tan, J., Wang, Y.: Resume mining of communities in social network. In: ICDM workshop, pp. 435–440 (2007)
Berger-Wolf, T.Y., Saia, J.: A framework for analysis of dynamic social networks. In: Proceedings of ACM SIGKDD, pp. 523–528 (2006)
Hopcroft, J., Khan, O., Kulis, B., Selman, B.: Tracking evolving communities in large linked networks. PNAS (2004)
Keogh, E., Lonardi, S., Ratanamahatana, C.A.: Towards parameter-free data mining. In: Proceedings of ACM SIGKDD, pp. 206–215 (2004)
Palla, G., Barabási, A., Vicsec, T.: Quantifying social group evolution. Nature 446 (2007)
Sun, J., Faloutsos, C., Papadimitriou, S., Yu, P.S.: Graphscope: parameter-free mining of large time-evolving graphs. In: Proceedings of ACM SIGKDD, pp. 687–696 (2007)
Backstrom, L., Huttenlocher, D., Kleinberg, J., Lan, X.: Group formation in large social networks: membership, growth, and evolution. In: Proceedings of ACM SIGKDD, pp. 44–54 (2006)
Leskovec, J., Kleinberg, J., Faloutsos, C.: Graphs over time:densification laws, shrinking diameters and possible explanations. In: Proceedings of ACM SIGKDD (2005)
Zhou, D., Councill, I.G., Zha, H., Giles, C.L.: Discovering temporal communities from social network documents. In: Perner, P. (ed.) ICDM 2007. LNCS (LNAI), vol. 4597, pp. 745–750. Springer, Heidelberg (2007)
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Wang, Y., Wu, B., Pei, X. (2008). CommTracker: A Core-Based Algorithm of Tracking Community Evolution. In: Tang, C., Ling, C.X., Zhou, X., Cercone, N.J., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2008. Lecture Notes in Computer Science(), vol 5139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88192-6_22
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DOI: https://doi.org/10.1007/978-3-540-88192-6_22
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