Analysis of evolving social network: methods and results from cell phone dataset case study

In this paper, we attempt to detect the changes in the structure of an evolving social network. We define a novel measure to quantify the dynamics of the network and use it to generate a timeline for the network that indicates the changes. We consider that any significant change in the network is as a result of occurrence of some event, and thus, identify the day or time step when the event took place. Further, the analysis involves identification of key individuals and their close associates that were active on that day. Finally, the case study involves identification of individuals having communication behaviour similar to the key individuals. To group such individuals, we use a recently proposed online clustering approach called evolving clustering (eClustering). We demonstrate the efficacy of the proposed quantification measures by conducting several experiments and comparing the results with the ground truth.

[1]  Harvey Thomas Banks,et al.  Dynamic social network models incorporating stochasticity and delays , 2010 .

[2]  A. Barabasi,et al.  Quantifying social group evolution , 2007, Nature.

[3]  Santo Fortunato,et al.  Community detection algorithms: a comparative analysis: invited presentation, extended abstract , 2009, VALUETOOLS.

[4]  B. Lewis,et al.  Transmission network analysis in tuberculosis contact investigations. , 2007, The Journal of infectious diseases.

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

[6]  Hsinchun Chen,et al.  Fighting organized crimes: using shortest-path algorithms to identify associations in criminal networks , 2004, Decis. Support Syst..

[7]  P. Angelov,et al.  Evolving Fuzzy Systems from Data Streams in Real-Time , 2006, 2006 International Symposium on Evolving Fuzzy Systems.

[8]  Yida Wang,et al.  On Mining Group Patterns of Mobile Users , 2003, DEXA.

[9]  R. Hanneman.  Introduction to Social Network Methods , 2001 .

[10]  Jean Scholtz,et al.  VAST 2008 Challenge: Introducing mini-challenges , 2008, 2008 IEEE Symposium on Visual Analytics Science and Technology.

[11]  Katy Howell.  An Introduction To Social Networks , 2015 .

[12]  John Scott.  Social Network Analysis , 1988 .

[13]  Derek Greene,et al.  Tracking the Evolution of Communities in Dynamic Social Networks , 2010, 2010 International Conference on Advances in Social Networks Analysis and Mining.

[14]  B Skyrms,et al.  A dynamic model of social network formation. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Plamen Angelov,et al.  Evolving Rule-Based Models: A Tool For Design Of Flexible Adaptive Systems , 2002 .

[16]  P. Angelov,et al.  Evolving rule-based models: A tool for intelligent adaptation , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

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

[18]  Yun Chi,et al.  Facetnet: a framework for analyzing communities and their evolutions in dynamic networks , 2008, WWW.

[19]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[20]  Matthew Richardson,et al.  Mining knowledge-sharing sites for viral marketing , 2002, KDD.

[21]  Bin Wu,et al.  Tracking the Evolution in Social Network: Methods and Results , 2009, Complex.

[22]  Jure Leskovec,et al.  Empirical comparison of algorithms for network community detection , 2010, WWW '10.

[23]  Gueorgi Kossinets,et al.  Empirical Analysis of an Evolving Social Network , 2006, Science.

[24]  Romain Bourqui,et al.  A Stable Decomposition Algorithm for Dynamic Social Network Analysis , 2009, EGC.

[25]  Jon Kleinberg,et al.  Maximizing the spread of influence through a social network , 2003, KDD '03.

[26]  Leandros Tassiulas,et al.  Social network analysis concepts in the design of wireless Ad Hoc network protocols , 2010, IEEE Network.

[27]  Matthew Richardson,et al.  Mining the network value of customers , 2001, KDD '01.