A predictive model of tourist destinations based on tourists' comments and interests using text analytics

• Published in: Tourism management perspectives Vol. 35; p. 100710
• Main Authors: Sohrabi, Babak, Raeesi Vanani, Iman, Nasiri, Narges, Ghassemi Rudd, Armin
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2020
• Subjects: Data mining; Iran; Predictive analysis; Text mining; Tourism; Tourism; Text mining; Predictive analysis; Iran; Data mining
• ISSN: 2211-9736; 2211-9744
• DOI: 10.1016/j.tmp.2020.100710

Data provided by tourists always benefit tourism managers and help them offer customized services, products and destinations to future travelers. This research investigates the effect of interests on Iranian outbound tourists, especially their selection of a destination and then, using text and data mining algorithms, it introduces a model to predict tourists' destinations based on their interests and travel backgrounds. In the current study, a dataset of 244,980 travels, consisting of 6661 people, was extracted from social media to discover the relationship between tourists' interests and travel destinations. Hence, it represents a model that is created using data and text mining from travel agencies to design their marketing plans by offering and advertising destinations to travelers with specific interest categories. The model has also shown promising accuracy and interesting results for the future tourist destination data and text analysis. •The personality aspects of tourists in relation to their preferences of destinations have rarely been studied•The results of this study can help the tourism-related organizations and tourists to have more customized services and offers.•The Clustering results show that the outbound Iranian tourists can be clustered into 4 categories.•By this information and more analysis on the data, the motivations of tourists can also be extracted.