Analysing User Reviews in Tourism with Topic Models
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.
KeywordsWeb 2.0 Customer reviews Classification
The first author wishes to acknowledge the financial support provided by the Australian Government Department of Education through the 2014 Endeavour Research Fellowship awarded for the visiting period at the Advanced Analytics Institute, University of Technology, Sydney, Australia, under the supervision of Prof. Longbing Cao.
Furthermore, authors acknowledge the financial support from the European Union (EU), the European Regional Development Fund (ERDF), the Austrian Federal Government and the State of Carinthia in the Interreg IV Italien-Österreich programme (project acronym O-STAR).
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