Automatic Classification of Forum Posts: A Finnish Online Health Discussion Forum Case

Abstract

Online health discussion forums play a key role in accessing, distributing and exchanging health information at an individual and societal level. Due to their free nature, using and regulating these forums require substantial amount of manual effort. In this study, we propose a computational approach, i.e., a machine learning framework, in order to categorize the messages from Finland’s largest online health discussion forum into 16 categories. An accuracy of 70.8% was obtained with a Naïve Bayes classifier, applied on term frequency-inverse document frequency features.