Abstract
In this article, we demonstrate the potential value that the spatial and semantic analysis of social media messages can provide to smart tourism ecosystems. Building upon a showcase of 600,000 Twitter messages in San Francisco, we illustrate insights for stakeholders within the tourism sector from various analyses, including kernel density estimation and latent Dirichlet allocation. We show that social media analytics captures spatial patterns within the city that relate to the presence of users and the environmental and topical engagement. Furthermore, we outline how these patterns serve as an input to value creation for smart urban tourism.
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