A Study on the Representation of the Various Models for Dynamic Social Networks

Abstract This paper describes the method of representation of the Dynamic Social Network. Authors begin the discussion with a formal introduction where they had brought out the need of the emergence of the Dynamic Social Network and its application in the various fields of science. Authors has carried forward the discussion with description of the two models of the Dynamic Social Network. Portions of the paper is a review work. In the followed section of this work, discussion is carried about how these models can be represented as one of the basic type of Finite State Machine. Finally the paper concludes with a real life example and the application of Dynamic Social Network in MANETS.

[1]  A. Agresti,et al.  Categorical Data Analysis , 1991, International Encyclopedia of Statistical Science.

[2]  Sanjeev Goyal,et al.  A Noncooperative Model of Network Formation , 2000 .

[3]  T. Snijders.  The statistical evaluation of social network dynamics , 2001 .

[4]  Tanya Y. Berger-Wolf,et al.  A framework for community identification in dynamic social networks , 2007, KDD '07.

[5]  A. Moore,et al.  Dynamic social network analysis using latent space models , 2005, SKDD.

[6]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  Christos Faloutsos,et al.  Graphs over time: densification laws, shrinking diameters and possible explanations , 2005, KDD '05.

[8]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[9]  Subrata Paul,et al.  A Review on some aspects of Black Hole Attack in MANET , 2014 .

[10]  V. Batagelj,et al.  Comparing resemblance measures , 1995 .

[11]  Peter D. Hoff,et al.  Latent Space Approaches to Social Network Analysis , 2002 .

[12]  Tanya Y. Berger-Wolf,et al.  A framework for analysis of dynamic social networks , 2006, KDD '06.

[13]  Padhraic Smyth,et al.  A Spectral Clustering Approach To Finding Communities in Graph , 2005, SDM.

[14]  Srinivasan Parthasarathy,et al.  An event-based framework for characterizing the evolutionary behavior of interaction graphs , 2007, KDD '07.

[15]  Jon M. Kleinberg,et al.  Group formation in large social networks: membership, growth, and evolution , 2006, KDD '06.

[16]  Volker Tresp,et al.  Soft Clustering on Graphs , 2005, NIPS.

[17]  Osmar R. Zaïane,et al.  Tracking changes in dynamic information networks , 2011, 2011 International Conference on Computational Aspects of Social Networks (CASoN).

[18]  Myra Spiliopoulou,et al.  Studying Community Dynamics with an Incremental Graph Mining Algorithm , 2008, AMCIS.

[19]  Randy Goebel,et al.  Local Community Identification in Social Networks , 2009, 2009 International Conference on Advances in Social Network Analysis and Mining.

[20]  P. Jaccard.  THE DISTRIBUTION OF THE FLORA IN THE ALPINE ZONE.1 , 1912 .