A fuzzy system-based approach to estimate the importance of online customer reviews

The indexed Web increases every day, making the development of automatic methods for knowledge extraction more relevant. The area of Sentiment Analysis or Opinion Mining aims to extract opinions from the user-generated content and to define the semantic orientation of each individual opinion. This work proposes an approach to estimate the degree of importance of comments generated by web users by using a Fuzzy system. The Fuzzy system has three inputs: author reputation, number of tuples <feature; quality word>, and percentage of correctly spelled words and one output: importance degree of the comment. The importance degree has been used to select the best comments in a Corpus. The paper also describes an experiment which was used to compare the results of a sentiment orientation method before and after the selection of the best comments. It was conducted with 1620 reviews also about smartphones (982 positives and 594 negatives) and our approach improved the results of sentiment orientation method up to approximately 10% in f-measure in positive reviews and 20% in f-measure in negative reviews.