A New Centrality Measure for Tracking Online Community in Social Network

Автор: Sanjiv Sharma, G.N. purohit

Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs

Статья в выпуске: 4 Vol. 4, 2012 года.

Бесплатный доступ

This paper presents a centrality measurement and analysis of the social networks for tracking online community. The tracking of single community in social networks is commonly done using some of the centrality measures employed in social network community tracking. The ability that centrality measures have to determine the relative position of a node within a network has been used in previous research work to track communities in social networks using betweenness, closeness and degree centrality measures. It introduces a new metric K-path centrality, and a randomized algorithm for estimating it, and shows empirically that nodes with high K-path centrality have high node betweenness centrality.

Еще

Social Network Analysis, Centrality, Communities

Короткий адрес: https://sciup.org/15011680

IDR: 15011680

Список литературы A New Centrality Measure for Tracking Online Community in Social Network

  • Garton L, Haythornthwaite C, Wellman B (1997) Studying online social networks. J Comput Mediated Commun 3(1):1–30.
  • L. Freeman. A set of measures of centrality based on betweenness.Sociometry, 40(1):35–41, 1977
  • Estrada E, Rodriguez-Velazquez AJ (2005) Subgraph centrality in complex networks. Phys Rev E 71:056103
  • Backstrom L (2006) Group formation in large social networks: membership, growth, and evolution. In: KDD 06: Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining, ACM Press, pp 44–54
  • Burt R (1982) Toward a structural theory of action: network models of social structure, perception and action. Academic, New York.
  • Carrington PJ, Scott J, Wasserman S (2006) Models and methods in social network analysis.Cambridge University Press, New York, NY, USA
  • Danon L, Duch J, Diaz-Guilera A, Arenas A (2005) Comparing community structure identification.J Stat Mech Theor Exp: P09008
  • Freeman CL (1978) Centrality in social networks: Conceptual clarification. Social Networks 1:215–239
  • Clauset A (2005) Finding local community structure in networks. Phys Rev E 72:026132
  • Du N, Wu B, Pei X, Wang B, Xu L (2007) Community detection in large-scale social networks.In WebKDD/SNA-KDD ’07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis. ACM, New York, NY, USA,pp 16–25
  • N. Friedkin. Horizons of observability and limits of informal control in organizations. Social Forces, 62(1):57–77, 1983.
  • G. Kahng, E. Oh, B. Kahng, and D. Kim. Betweenness centrality correlation in social networks. Phys. Rev. E, 67:01710–1, 2003.
  • Danon L, Duch J, Diaz-Guilera A, Arenas A (2005) Comparing community structure identification.J Stat Mech Theor Exp: P09008
  • M. Newman. A measure of betweenness centrality based on random walks. Social Networks, 27(1):39–54, 2005.
  • K. Stephenson and M. Zelen. Rethinking centrality: Methods and examples. Social Networks, 11:1–37, 1989.
  • Newman EJM, Girvan M (2004) Finding and evaluating community structure in networks.Phys Rev E 69:026113
  • Ruhnau B (October 2000) Eigenvector-centrality – a node-centrality? Social Networks 22(4):357–365
  • Fortunato S, Latora V, Marchiori M (2004) Method to find community structures based on information centrality. Phys Rev E (Stat Nonlinear, Soft Matter Phys) 70(5):056104
  • Radicchi F, Castellano C, Cecconi F, Loreto V, Parisi D (2004) Defining and identifying communities in networks. Proc Natl Acad Sci USA 101(9):2658–2663
  • Tantipathananandh C, Berger-Wolf YT, Kempe D (2007) A framework for community identification in dynamic social networks. In: KDD ’07: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, New York, NY,USA, pp 717–726
  • Traud LA, Kelsic DE, Mucha JP, Porter AM (2009) Community structure in online collegiate social networks, American Physical Society, 2009 APS March Meeting, March 16–20, pp.
  • U. Brandes. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2):163–177, 2001.
  • U. Brandes and C. Pich. Centrality estimation in large networks.I. J. of Bifurcation and Chaos, 17(7):2303–2318, 2007.
  • Borgatti SP, Everett GM, Freeman CL (2002) Ucinet for windows: software for social network analysis. Analytic Technologies, Harvard, USA Science BV, Amsterdam, the Netherlands, pp 107–117.
  • de Nooy W, Mrvar A, Batagelj V (2005) Exploratory social network analysis with pajek.Cambridge University Press, New York, USA.
Еще
Статья научная