Classification of Customer Reviews based on Sentiment Analysis

In this paper we propose a system that performs the classification of customer reviews of hotels by means of a sentiment analysis. We elaborate on a process to extract a domain-specific lexicon of semantically relevant words based on a given corpus (Scharl et al., 2003; Pak & Paroubek, 2010). The resulting lexicon backs the sentiment analysis for generating a classification of the reviews. The evaluation of the classification on test data shows that the proposed system performs better compared to a predefined baseline: if a customer review is classified as good or bad the classification is correct with a probability of about 90%.