The sustainable management of overtourism via user content
Concepción Foronda Robles et al.
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. • Overtourism affects sustainability by causing environmental degradation. • Tourist flow management mitigates congestion and preserves local heritage. • The evaluation of cost perception is decisive for balanced tourism development. • User satisfaction and spatial significance are key dimensions. • Online reviews reveal patterns of dissatisfaction and unsustainability.
8 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.70 × 0.15 = 0.10 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.