The sustainable management of overtourism via user content

Abstract

This research evaluates impacts of overtourism in Granada, Spain, by analysing 1349 negative comments from TripAdvisor for 71 tourist attractions. Employing a mixed-methods approach, the study uses sentiment analysis via the BERT model, multivariate analysis (PCA and K-means clustering) and social network analysis. Key findings reveal issues of congestion, high costs and environmental degradation, identifying user satisfaction and spatial significance as critical dimensions. The study highlights a strong positive correlation between AI-driven sentiment and user opinions. Practical implications underscore the need for sustainable management strategies—including destination diversification, improved transport networks and access control—to mitigate highly touristified environments, preserve visitor experience and protect local heritage, thereby promoting sustainable tourism. Online reviews are deemed valuable for proactively addressing tourist concerns.