Community Event Prediction in Dynamic Social Networks

Ilhan N., Öğüdücü Ş.

12th International Conference on Machine Learning and Applications (ICMLA), Florida, Amerika Birleşik Devletleri, 4 - 07 Aralık 2013, ss.191-196 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/icmla.2013.40
  • Basıldığı Şehir: Florida
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.191-196
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

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.