Abstract
In tourism studies, new means of data collection are opening up opportunities for disclosing hidden mobility patterns. This paper aims to analyze and model the tourist flow networks for different lengths of trip on urban scale, using user generated content (UGC) data collated from an open tourism web service. The textual UGC data, with high spatial and temporal resolution, is utilized to construct three tourist flow networks in response to length of trips. Social network analysis and a revised spatial interaction model are deployed for exploring the temporal heterogeneity in the tourist movements. This empirical study from Nanjing City has further confirmed the power law of distance decay in intraurban tourist mobility. Furthermore, the research reveals temporal variations with length of trip. The paper highlights the role of time in the tourism study through incorporating a temporal dimension into the analyses and taking advantage of the availability of new data.
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