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Social media analysis is a powerful tool for tourism research that, at a relatively low cost, can be used to manage and process large datasets of comments, ratings, and shares from different online communities. However, the heterogeneous nature of unsolicited opinions, the complexity of natural language assessment, and differences in the characteristics of social-data sources hinder the accurate assessment of preferences. However, the use of solicited data sources, such as direct polling, is typically resource-intensive, time-consuming, and geographically limited. We analyze a hybrid approach that combines active polling with passive social media analysis to rate tourist experience. To this end, we present a novel multiple criteria decision analysis model for preference-extraction from solicited and unsolicited data. The proposed approach can significantly reduce the number of polls required to accurately assess the preferences of a community.

Hybrid preference assessment for tourism research using solicited and unsolicited opinions: an application in rural tourism