Analysing user reviews in tourism with topic models
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User generated content in general and textual reviews in particular constitute a vast source of information for the decision making of tourists and management and are therefore a key component for e-tourism. This paper explores different application scenarios for the topic model method to process these textual reviews in order to provide accurate decision support and recommendations as well as to build a basis for further analytics. Besides contributing a new model based on the topic model method, this paper also includes empirical evidence from experiments on user reviews from the YELP dataset and from TripAdvisor.
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