Hotel Rating Prediction System Based on Time Factors

Abstract

While the internet provides abundant information, it often leads to information overload of users when purchasing goods. Tripadvisor.com, despite having a date sorting function, struggles to effectively filter relevant comments to users and neglects that consumer preferences may change over time. Therefore, this study aims to develop a website with visual charts showing changes in sentiment over time in reviews. The goal is to determine if this website improves user efficiency compared to the original website, reducing search time and aiding decision-making. The chart generation process involves four stages: collecting and preprocessing comments, constructing a hotel feature dictionary, classifying sentences and computing sentiment scores, and embedding charts on the website. 36 Tripadvisor.com users participate in experiments to evaluate the impact of old and new interfaces on answer quantity and search time. The NASA.tlx scale is used to assess the mental load experienced with both interfaces.