Text message categorization of collaborative learning skills in online discussion using support vector machine

Abstract

This paper presents a method for text messages categorization of collaborative learning skills in online discussion. Despite of support vector machine is a popular method for text categorization in the research area of machine learning, unfortunately, the use of support vector machine in an educational setting is rare. Usually, text categorization by support vector machine is employed to categorize news article, emails, product reviews and web pages. In an online discussion, text categorization that used to classify the message send by student into a certain category is often manual, requiring human skilled specialists. However, human categorization is not an effective way for number of reasons; time-consuming, labor intensive, lack of consistency in category and costly. Therefore, this paper proposes support vector machine approach to automatic code the message. Results show that support vector machine achieving good classification on eight categories of collaborative learning skill in online discussion as measured based on the error rate, precision, recall and balanced F-measure.