Regression Analysis of Tourist Photographic Activity Using Geo-tagged Photos and GPS Trajectory

Nowadays, many photos are posted on social photo sharing web sites (e.g. Flickr, Instagram). The number of the shared geo-tag photos in a certain attraction does not correlate to the number of visitors because the photographic activity is influenced by multiple factors. The estimation of the number of tourists in a certain attraction from the geo-tagged photos is useful for marketing and tourism policy making. In this paper, from the viewpoint of tourism information, we propose a photographic activity model to estimate the number of tourists in the attraction and examine the model by using the regression analysis. We analyze the dataset consists of GPS trajectory and the photographic history of foreign tourists who traveled in Kyoto area in Japan. As the results, we show that the proposed photographic activity model indicates high goodness-of-fit and correlation to the dataset.