Community Event Prediction in Dynamic Social Networks


Ilhan N. , Öğüdücü Ş.

12th International Conference on Machine Learning and Applications (ICMLA), Florida, United States Of America, 4 - 07 December 2013, pp.191-196 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icmla.2013.40
  • City: Florida
  • Country: United States Of America
  • Page Numbers: pp.191-196

Abstract

Communities are fundamental units of every social network; their structure and evolution are essential to understanding the structure and functionality of large networks. Also, community evolution prediction is an important task with various real-life applications in social network analysis. In this paper, we present a framework for modeling community evolution prediction in social networks. Each community is characterized by a wide range of structural features to describe community characteristics and a series of evolutionary events. A community matching algorithm is also proposed to efficiently identify and track similar communities over time. Experiments on different data sets prove that a high rate of community evolution prediction has been achieved.