Community Detection in Social Networks Considering Topic Correlations

Authors

  • Yingkui Wang Tianjin University
  • Di Jin Tianjin University
  • Katarzyna Musial University of Technology Sydney
  • Jianwu Dang Tianjin University

DOI:

https://doi.org/10.1609/aaai.v33i01.3301321

Abstract

Network contents including node contents and edge contents can be utilized for community detection in social networks. Thus, the topic of each community can be extracted as its semantic information. A plethora of models integrating topic model and network topologies have been proposed. However, a key problem has not been resolved that is the semantic division of a community. Since the definition of community is based on topology, a community might involve several topics. To ach

Downloads

Published

2019-07-17

How to Cite

Wang, Y., Jin, D., Musial, K., & Dang, J. (2019). Community Detection in Social Networks Considering Topic Correlations. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 321-328. https://doi.org/10.1609/aaai.v33i01.3301321

Issue

Section

AAAI Technical Track: AI and the Web