Changes in the spatial and temporal characteristics of inbound tourism flows in Tibet based on geotagged photographs

Abstract

With the further advent of the era of big data, the scale of social media data containing geolocation information is exploding, providing a new source of big data information and perspective for an in-depth study of the changing spatio-temporal and geographical characteristics of the current tourist population. This paper extracts data on popular attractions in the Tibet Autonomous Region using the HDBSCAN algorithm combined with the TF-IDF algorithm based on information on images with geotags shared by users in the Flickr image sharing site from 2005-2018. Social network analysis was used to explore the changes in the spatial and temporal characteristics of inbound tourism flows in Tibet. The results show that: (1) in terms of temporal characteristics, the number of inbound tourists shows obvious off-peak seasons, with relatively high sensitivity to the influence of economic, policy and infrastructure construction factors; (2) in terms of spatial distribution characteristics, the inbound tourism flow in Tibet shows an "axis-scattered"distribution. The core area is centred on Lhasa and extends in three directions: west, north and east along important roads.