From reviews to value: harnessing crowdsourced data to capture visitor perceptions and economic benefits of recreation

Quantifying the recreational value of protected natural areas is essential for sustainable management, conservation financing, and informed decision-making. Traditional approaches, such as on-site surveys, are often costly, spatially limited, and constrained by regulatory barriers. This study evaluates the potential of crowdsourced user-generated data to jointly assess visitor perceptions and the economic value of nature-based recreation, using Back Bay National Wildlife Refuge (Virginia, USA) as a case study. We integrated georeferenced photographs and textual content from four platforms (Flickr, TripAdvisor, Yelp, and AllTrails) with supplementary survey data to analyze visitation patterns, visitor sentiment, cultural ecosystem services, and recreational value using the travel cost method. Sentiment analysis revealed predominantly positive visitor perceptions, particularly associated with aesthetic appreciation, wildlife encounters, and recreation. Crowdsourced data identified 1,289 visits with known visitor origins, capturing a broader and more geographically diverse population than surveys alone. Travel cost estimates derived from crowdsourced data yielded an average per-trip cost of US$527, compared to US$91 from surveys, resulting in an annual recreational value of US$74.7 million versus US$13.0 million. These findings demonstrate that integrating multiple crowdsourced platforms enhances recreation assessment along two complementary dimensions: the experiential dimension, defined as the subjective quality of visitor experiences captured through sentiment analysis, and the economic dimension, quantified through travel cost modeling to estimate recreational value. This approach expands spatial coverage, improves origin characterization, and offers a scalable, cost-effective complement to traditional methods for valuing nature-based recreation.