Sentiment Analysis of Hotel Reviews in Greek: A Comparison of Unigram Features

Abstract

Web 2.0 has become a very useful information resource nowadays, as people are strongly inclined to express online their opinion in social media, blogs and review sites. Sentiment analysis aims at classifying documents as positive or negative according to their overall expressed sentiment. In this paper, we create a sentiment classifier applying Support Vector Machines on hotel reviews written in Modern Greek. Using a unigram language model, we compare two different methodologies and the emerging results look very promising.