Aspect-based Sentiment Analysis on Hotel Reviews
نویسنده
چکیده
In this project we explored varieties of supervised machine learning methods for the purpose of sentiment analysis on TripAdvisor hotel reviews. We experimented and explored with the factors that affect accuracy of the predictions to develop a satisfying review analyzer. We focus on not only the overall opinions but also aspect based opinions including service, rooms, location, value, cleanliness, sleep quality and business service. As a result, we implemented an analyzer that is able to predict rating and polarity of reviews on individual aspects. The accuracy of our predictors reached 70% to 75% for star-rating and about 85% to 90% for polarity.
منابع مشابه
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