A Fuzzy Synthetic Evaluation Approach to Assess Usefulness of Tourism Reviews by Considering Bias Identified in Sentiments and Articulacy

Abstract

Assessing the usefulness of reviews has been the aim of several research studies. However, results regarding the significance of usefulness determinants are often contradictory, thus decreasing the accuracy of reviews’ helpfulness estimation. Also, bias in user reviews attributed to differences, e.g., in gender, nationality, etc., may result in misleading judgments, thus diminishing reviews’ usefulness. Research is needed for sentiment analysis algorithms that incorporate bias embedded in reviews, thus improving their usefulness, readability, credibility, etc. This study utilizes fuzzy relations and fuzzy synthetic evaluation (FSE) in order to calculate reviews’ usefulness by incorporating users’ biases as expressed in terms of reviews’ articulacy and sentiment polarity. It selected and analyzed 95,678 hotel user reviews from Tripadvisor, written by users from five specific nationalities. The findings indicate that there are differences among nationalities in terms of the articulacy and sentiment of their reviews. The British are most consistent in their judgments expressed in titles and the main body of reviews. For the British and the Greeks, review titles suffice to convey any negative sentiments. The Dutch use fewer words in their reviews than the other nationalities. This study suggests that fuzzy logic captures subjectivity which is often found in reviews, and it can be used to quantify users’ behavioral differences, calculate reviews’ usefulness, and provide the means for developing more accurate voting systems.