Abstract
A social network is an abstract concept consisting of set of people and relationships linking pairs of humans. A new multidimensional model, which covers three main dimensions: relation layer, time window and group, is proposed in the paper. These dimensions have a common set of nodes, typically, corresponding to human beings. Relation layers, in turn, reflect various relationship types extracted from different user activities gathered in computer systems. The time dimension corresponds to temporal variability of the social network. Social groups are extracted by means of clustering methods and group people who are close to each other. An atomic component of the multidimensional social network is a view – small social sub-network, which is in the intersection of all dimensions. A view describes the state of one social group, linked by one type of relationship (one layer), and derived from one time period. The multidimensional model of a social network is similar to a general concept of data warehouse, in which a fact corresponds to a view. Aggregation possibilities and usage of the model is also discussed in the paper.
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References
Agarwal, N., Galan, M.H., Liu, H., Subramanya, S.: WisColl: Collective Wisdom based Blog Clustering. Information Sciences 180(1), 39–61 (2010)
Blondel, V.D., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech., 10008 (2008)
Bródka, P., Musial, K., Kazienko, P.: A method for group extraction in complex social networks. In: Lytras, M.D., Ordonez De Pablos, P., Ziderman, A., Roulstone, A., Maurer, H., Imber, J.B. (eds.) WSKS 2010. CCIS, vol. 111, pp. 238–247. Springer, Heidelberg (2010)
Cheng, X., Dale, C., Liu, J.: Statistics and social networking of YouTube videos. In: Proc. the 16th International Workshop on Quality of Service, pp. 229–238. IEEE, Los Alamitos (2008)
Chiu, P.Y., Cheung, C.M.K., Lee, M.K.O.: Online Social Networks: Why Do "We" Use Facebook? In: The First World Summit on the Knowledge Society. Communications in Computer and Information Science, vol. 19, pp. 67–74. Springer, Heidelberg (2008)
Ellison, N.B., Steinfield, C., Lampe, C.: The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. J. of Computer-Mediated Communication 12 (4) (2007), http://jcmc.indiana.edu/vol12/issue4/ellison.html
Flament, C.: Application of graph Theory to Group Structure. Prentice-Hall, Englewood Cliffs (1963)
Garton, L., Haythorntwaite, C., Wellman, B.: Studying Online Social Networks. Journal of Computer-Mediated Communication 3(1), 75–105 (1997)
Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. The National Academy of Sciences, USA 99(12), 7821–7826 (2002)
Golbeck, J., Hendler, J.: FilmTrust: movie recommendations using trust in web-based social networks. In: IEEE Conference Proceedings on Proc. Consumer Communications and Networking Conference, vol. 1, pp. 282–286 (2006)
Hanneman, R., Riddle, M.: Introduction to social network methods. Online textbook. University of California, Riverside (2005), http://faculty.ucr.edu/~hanneman/nettext/
Huberman, B., Romero, D., Wu, F.: Social networks that matter: Twitter under the microscope. First Monday, 1–5 (2009)
Jung, J.J.: Query transformation based on semantic centrality in semantic social network. Journal of Universal Computer Science 14(7), 1031–1047 (2008)
Kazienko, P., Musial, K., Kajdanowicz, T.: Multidimensional Social Network and Its Application to the Social Recommender System. IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans 41(4) (2011) (in press)
Kazienko, P., Musial, K., Kajdanowicz, T.: Profile of the Social Network in Photo Sharing Systems. In: AMCIS 2008, Association for Information Systems, AIS (2008)
Kazienko, P., Musiał, K., Zgrzywa, A.: Evaluation of Node Position Based on Email Communication. Control and Cybernetics 38(1), 67–86 (2009)
Kazienko, P., Ruta, D., Bródka, P.: The Impact of Customer Churn on Social Value Dynamics. Int. J. of Virtual Communities and Social Networking 1(3), 60–72 (2009)
Scott, J.: Social Network Analysis: A Handbook. SAGE Publications, London (2000)
Sulo, R., Berger-Wolf, T., Grossman, R.: Meaningful Selection of Temporal Resolution for Dynamic Networks. In: MLG 2010, ACM, New York (2010)
Wasserman, S., Faust, K.: Social network analysis: Methods and applications. Cambridge University Press, New York (1994)
Watts, D.J., Strogatz, S.: Collective dynamics of ’small-world’ networks. Nature 393, 440–444 (1998)
Wellman, B., Salaff, J., Dimitrova, D., Garton, L., Gulia, M., Haythornthwaite, C.: Computer Networks as Social Networks: Collaborative Work, Telework, and Virtual Community. Annual Review of Sociology 22(1), 213–238 (1996)
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Kazienko, P., Musial, K., Kukla, E., Kajdanowicz, T., Bródka, P. (2011). Multidimensional Social Network: Model and Analysis. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6922. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23935-9_37
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DOI: https://doi.org/10.1007/978-3-642-23935-9_37
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