Clustering Student Discussion Messages on Online Forumby Visualization and Non-Negative Matrix Factorization

Xiaodi Huang, Jianhua Zhao, Jeff Ash, Wei Lai

Faculty of Education Information Technology, South China Normal University, China.
Faculty of Information and Communication Technologies Swinburne University of Technology, Australia.
School of Computing and Mathematics, Charles Sturt University, Australia.

DOI: 10.4236/jsea.2013.67B002                

Abstract

The use of online discussion forum can effectively engage students in their studies. As the number of messages posted on the forum is increasing, it is more difficult for instructors to read and respond to them in a prompt way. In this paper, we apply non-negative matrix factorization and visualization to clustering message data, in order to provide a summary view of messages that disclose their deep semantic relationships. In particular, the NMF is able to find the underlying issues hidden in the messages about which most of the students are concerned. Visualization is employed to estimate the initial number of clusters, showing the relation communities. The experiments and comparison on a real dataset have been reported to demonstrate the effectiveness of the approaches.

Keywords

Online Forum; Cluster; Non-Negative Matrix Factorization; Visualization

Conflicts of Interest

The authors declare no conflicts of interest.

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