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A social media analysis of travel preferences and attitudes,before and during Covid-19
Affiliation:Copenhagen Business School, Department of Management, Society & Communication, Dalgas Have 15, DK-2000, Frederiksberg, Denmark
Abstract:
Covid-19 created tremendous uncertainty in the tourism industry; in this study, we use social media data to explore differences in the preferences and attitudes of tourism consumers, both before and during the pandemic. We use natural language processing (NLP) techniques to analyze over one million Reddit posts on travel-related subreddits. We investigate the preference for city and nature-oriented tourism in selected destinations; the analysis demonstrates that nature tourism gained interest during Covid-19 in destinations with rich nature resources, whereas city tourism lost interest in destinations known for city tourism. We also classify Reddit authors into two categories: conservation and openness, according to a psychological theory of personal values, and show that this is predictive, with openness associated with positive travel sentiment and low risk awareness. This points to the potential for value-based segmentation of travel consumers based on theoretically-grounded NLP analysis of social media data.
Keywords:Covid-19  Crisis management  Risk awareness  Travel sentiment  Travel preference  Social media  Text mining  Natural language processing
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