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Abstrakty
Social network analysis (SNA) is an important and valuable tool for knowledge extraction from massive and unstructured data. Social network provides a powerful abstraction of the structure and dynamics of diverse kinds of interpersonal connection and interaction. In this paper, we address issues associated with the application of SNA to the investigation and analysis of social relationships of people. We provide a brief introduction to representation and analysis of social networks, SNA models and methods. The main objective is to investigate the application of SNA techniques to data mining in case of two social networks Facebook and Twitter. The presented simulations illustrate how social analysis can be used to determine the interpersonal connections, importance of actors in a given social network and detect communities of people. We then discuss strength and weakness of SNA techniques.
Rocznik
Tom
Strony
83--91
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
autor
- Institute of Control and Computation Engineering, Warsaw University of Technology, Warsaw, Poland, M.Mincer@stud.elka.pw.edu.pl
Bibliografia
- [1] S. N. Dorogovtsev and J. F. F. Mendes, “Evolution of networks”, Advances Phys., vol. 51, no. 4, pp. 1079–1187, 2002.
- [2] W. Gruszczyński and P. Arabas, “Application of social network to improve effectiveness of classifiers in churn modelling”, in Proc. 3rd Int. Conf. Comput. Aspects of Social Netw. CASoN’11, Salamanca, Spain, 2011.
- [3] M. Kamola, B. C. Piech, and E. Niewiadomska-Szynkiewicz, “Re- construction of a social network graph from incomplete call detail records”, in Proc. 3rd Int. Conf. Comput. Aspects of Social Netw. CASoN’11, Salamanca, Spain, 2011.
- [4] M. E. J. Newman, “Modularity and community structure in networks”, Proc. Nat. Academy Sci. USA, vol. 103, no. 23, pp. 8577–8582, 2006.
- [5] M. E. J. Newman, A. L. Barabasi, and D. J. Watts, The Structure and Dynamics of Networks. USA: Princeton University Press, 2006.
- [6] M. E. J. Newman, “Communities, modules and large-scale structure in networks”, Nature Phys., vol. 8, pp. 25–31, 2011.
- [7] S. Wasserman and K. Faust, Social Network Analysis. USA: Camridge University Press, 2009.
- [8] S. Eubank, H. Guclu, V. S. A. Kumar, M. V. Marathe, A. Srinivasan, Z. Toroczkaj, and N. Wang, “Modelling disease outbreaks in realistic urban social networks”, Nature, vol. 429, pp. 180–183, 2004.
- [9] A. D. Henry, “Belief-oriented segregation in policy networks”, Procedia – Social Behav. Sci., vol. 22, pp. 14–26, 2011.
- [10] B. Karrer and M. E. J. Newman, “Competing epidemics on complex networks”, Phys. Rev., vol. 84, pp. 1–14, 2011.
- [11] S. L. Magsino, Applications of Social Network Analysis for Building Community Disaster Resilience. USA: The National Academies Press, 2009.
- [12] M. A. Porter, P. J. Mucha, M. E. J. Newman, and A. J. Friend, “Community structure in the united states house of representatives”, Physica, vol. 386, pp. 414–438, 2007. 90
- [13] Z. Tarapata and R. Kasprzyk, Graph-based optimization method for information diffusion and attack durability in networks. Lecture Notes Artif. Intel., vol. 6086, pp. 698–709, 2010.
- [14] V. D. Blondel, J. L. Guillaume, R. Lambiotte, and E. Lefebvre, “Fast unfolding of communities in lagre networks”, J. Statistical Mechanics: Theory and Experiment, no. 10, pp. 1–12, 2008.
- [15] S. P. Borgatti, “Centrality and network flow”, Social Netw., vol. 27, pp. 55–71, 2005.
- [16] A. Clauset, M. E. J. Newman, and C. Moore, “Finding community structure in very large networks”, Rev. Modern Phys., vol. 70, pp. 66–111, 2004.
- [17] A. Fronczak and P. Fronczak, Świat sieci złożonych. Od fizyki do Internetu. Warsaw: PWN, 2009 (in Polish).
- [18] D. Watts, “Networks, dynamics and the small-world phenomenon”, The American J. of Sociol., vol. 105, no. 2, pp. 493–527, 1999.
- [19] R. Albert and A. L. Barabási, “Statistical mechanics of complex networks”, Rev. Modern Phys., vol. 47, pp. 47–97, 2002.
- [20] A. L. Barabási and R. Albert, “Emergence of scaling in random networks”, Science, vol. 286, pp. 509–512, 1999.
- [21] S. Boccaletti, M. Ivanchenko, V. Latora, A. Pluchino, and A. Rapisarda, “Detecting complex network modularity by dynamical clustering”, Phys. Rev., vol. 75, no. 4, pp. 1–4, 2007.
- [22] M. Girvan and M. E. J. Newman, “Community structure in social and biological networks”, Proc. Nat. Academy Sci. USA, vol. 99, no. 12 pp. 7821–7826, 2002.
- [23] A. J. Enright, S. Van Dongen, and C. A. Ouzounis, “An efficient algorithm for large-scale detection of protein families”, Nucleic Acid Res., vol. 30, no. 7, pp. 1575–1584, 2002.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BATA-0016-0010