Abstract
Social network is a structure in which nodes are a set of social actors that are connected together by different types of relationships. Because of the complexity of the actors and the relationships between actors, social networks are always represented by weighted, labeled and directed graph. Social network analysis (NSA) is a set of techniques for determining and measuring the magnitude of the pressure. Social network analysis is focused also on visualization techniques for exploring the networks structure. It has gained a significant following in many fields of applications. It has been used to examine how the problems have been solved, how organizations interact with others, to understand the role of an individual in an organization… In this paper, we focus on two methods: 1- graphs visualization; 2- network analysis based on graph vertices comparison.
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References
Wasserman, S., Faust, K.: Social network analysis in the social and behavioral sciences. In: Social Network Analysis: Methods and Applications, pp. 1–27. Cambridge University Press (1994). ISBN 9780521387071
Scott, J.: Social Network Analysis. Sage, Newbury Park (1992)
Gajer, P., Kobourov, S.G.: GRIP: Graph dRawing with Intelligent Placement. In Marks, J. (ed.) Proceedings of the Graph Drawing, pp. 222–228. Colonial Wiliamsburg (2001)
Fruchterman, T.M.J., Reingold, E.M.: Graph drawing by force-directed placement. Softw. Pract. Exp. 21(11), 1129–1164 (1991)
Kamada, T., Kawai, S.: An algorithm for drawing general undirected graphs. Inf. Process. Lett. 31(1), 7–15 (1989)
Ho, J., Hong, S.-H., Gronemann, M., Jünger, M.: Drawing Clustered Graphs as Topographic Maps. In: Didimo, W., Patrignani, M. (eds.) GD 2012. LNCS, vol. 7704, pp. 426–438. Springer, Heidelberg (2013)
Chuang, J.-H., Lin, C.-C., Yen, H.-C.: Drawing graphs with nonuniform nodes using potential fields. In: Liotta, G. (ed.) GD 2003. LNCS, vol. 2912, pp. 460–465. Springer, Heidelberg (2004)
Eades, P., Huang, M.L.: Navigating clustered graphs using force-directed methods. J. Graph Algorithms Appl. 4, 157–181 (2000)
Truong, Q.D., Dkaki, T., Mothe, J., Charrel, P-J.: GVC: a graph-based information retrieval model. In: Conférence francophone en Recherche d’Information et Applications (CORIA 2008), Trégastel (France), 12–14 Mar 2008, pp. 337–351. CNRS (2008)
Blondel, V.D., Gajardo, A., Heymans, M., Senellart, P., Van Dooren, P.: A measure of similarity between graph vertices: applications to synonym extraction and web searching. SIAM Rev. 46(4), 647–666 (2004)
Melnik, S., Garcia-Molina, H., Rahm, E.: Similarity flooding: a versatile graph matching algorithm and its application to scheme matching. In: Proceedings of the 18th ICDE Conference (2002)
Biedl, T.C., Brandenburg, F.J.: Graph-Drawing Contest Report. In: Mutzel, P., Jünger, M., Leipert, S. (eds.) GD 2001. LNCS, vol. 2265, pp. 513–521. Springer, Heidelberg (2002)
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Truong, Q.D., Truong, Q.B., Dkaki, T. (2016). Graph Methods for Social Network Analysis. In: Vinh, P., Barolli, L. (eds) Nature of Computation and Communication. ICTCC 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 168. Springer, Cham. https://doi.org/10.1007/978-3-319-46909-6_25
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DOI: https://doi.org/10.1007/978-3-319-46909-6_25
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