Social Media Analysis via Network Approaches

Social media such as online forum and weblog are composed of dense interactions between user and content where network models are often appropriate for analysis. Using Markov logic network, user participation models can be developed to help us gain insights on the latent base topics of online discussions. Furthermore, joint non-negative matrix factorization model of participation and content data which can be viewed as a bipartite graph model between users and media. The factorizations allows simultaneous automatic discovery of leaders and sub-communities in the online forum as well as the core latent topics in the forum. Results on topic detection of online forums as well as the clustering analysis are given. Part of this work is based on a copyright-free paper that received Best Workshop Paper Award in 2007 IEEE International Conference on EBusiness Engineering Student Workshop.