Exploring Online Travel Reviews Using Data Analytics: An Exploratory Study

The information provided by online traveler reviews is becoming a key element in the decision-making process of hotel customers, reducing the uncertainty and the perceived risk of a traveler. Therefore, a careful analysis of the content provided by online customers’ reviews might give invaluable information concerning the key determinants, from a user’s perspective, of the quality of the service provided, justifying the attributed service rating. The objectives of this study are twofold: (1) use text-mining techniques to analyze the user’s generated content automatically collected from hotels in Porto in a certain period of time and, from this analysis, derive the most frequent terms used to describe the service; (2) understand whether it is possible to predict the aggregated rating assigned by reviewers based on the terms used and, at the same time, identify the terms showing high predictive capacity. Our study attempts to support hotel service managers in achieving their strategic and tactical goals by using innovative text- and data-mining tools to explore the wealth of information provided by user generated content in an easy and timely way.