An Evaluation of Automatic Text Categorization in Online Discussion Analysis

Content analysis is often employed by teachers and research to analyse online discussion forums to serve various purposes such as assessment, evaluation, and educational research. Automating content analysis is desirable so that such analysis can be carried out efficiently on large amount of data. This paper evaluates text categorization and examines whether the attainable accuracy can satisfy the requirements of common content analysis tasks. It shows that even simple text categorization techniques can support tasks such as online learning progress monitoring. Methods of augmenting text categorization with other techniques are also discussed.