Using sentiment text analysis of user reviews in social media for e-tourism mobile recommender systems

This paper describes main modern tendencies for the design and development of e-tourism recommender systems with sentiment analysis of user generated content in social media. Main goal is to systematize and summarize knowledge about the possibilities of using tourist’s user reviews in social media as a type of e-tourism big data for mobile e-tourism recommender systems. In particular, to analyze the sources and types of tourist feedback data, messages and comments generated by the tourist with his gadget that can be related to etourism big data. Developing efficient tools for e-tourism user comments and feedback in social media, combining big data technologies, NLP and smartphone services advantages, can provide e-tourism recommender systems with new better ways of creating more personalized recommendations.