Constructing Thai Opinion Mining Resource: A Case Study on Hotel Reviews

Opinion mining and sentiment analysis has recently gained increasing attention among the NLP community. Opinion mining is considered a domaindependent task. Constructing lexicons for different domains is labor intensive. In this paper, we propose a framework for constructing Thai language resource for feature-based opinion mining. The feature-based opinion mining essentially relies on the use of two main lexicons, features and polar words. Our approach for extracting features and polar words from opinionated texts is based on syntactic pattern analysis. The evaluation is performed with a case study on hotel reviews. The proposed method has shown to be very effective in most cases. However, in some cases, the extraction is not quite straightforward. The reasons are due to, firstly, the use of conversational language in written opinionated texts and, secondly, the language semantic. We provide discussion with possible solutions on pattern extraction for some of the challenging cases.