Complaint Sentence Detection via Automatic Training Data Generation using Sentiment Lexicons and Context Coherence

Abstract

We propose an automatic method for detecting complaint sentences from review documents. The proposed method consists of two procedures. One is a data generation procedure using sentiment lexicons and context coherence and the other is the expansion of a naive Bayes classifier based on the characteristics of the training data. This method has an advantage of not requiring human effort for the creation of large-scale training data and management of rules for complaint detection. The experimental results indicate that this method is more effective than the baseline methods.