Tracking Group Evolution in Social Networks

Easy access and vast amount of data, especially from long period of time, allows to divide social network into timeframes and create temporal social network. Such network enables to analyse its dynamics. One aspect of the dynamics is analysis of social communities evolution, i.e., how particular group changes over time. To do so, the complete group evolution history is needed. That is why in this paper the new method for group evolution extraction called GED is presented.

[1]  Philip S. Yu,et al.  GraphScope: parameter-free mining of large time-evolving graphs , 2007, KDD '07.

[2]  Katarzyna Musial,et al.  User position measures in social networks , 2009, SNA-KDD '09.

[3]  Deepayan Chakrabarti,et al.  Evolutionary clustering , 2006, KDD '06.

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

[5]  Przemyslaw Kazienko,et al.  Group Evolution Discovery in Social Networks , 2011, 2011 International Conference on Advances in Social Networks Analysis and Mining.

[6]  Jiawei Han,et al.  A Particle-and-Density Based Evolutionary Clustering Method for Dynamic Networks , 2009, Proc. VLDB Endow..