TripAdvisor Review Sentiment Mining

TripAdvisor review sentiment mining applies opinion mining and sentiment analysis to the large volumes of online reviews that travellers write about hotels, restaurants and attractions on platforms such as TripAdvisor. Grounded in the opinion-mining methodology surveyed by Pang and Lee (2008), it uses lexicon-based or machine-learning text classifiers to determine whether a review, sentence or opinion is positive, negative or neutral, turning unstructured free text into structured sentiment data. Applied to hospitality, as demonstrated by Xiang and colleagues (2015) in their big-data analysis of hotel guest experience, the technique can go beyond an overall verdict to extract aspect-level sentiment, revealing how guests feel about specific facets like room, service, location, value and cleanliness. The result is a scalable way to read what thousands of guests are actually saying and to quantify the tone of a property's online reputation.