Analyzing factors on tourist movement predictability: a study based on social media data

Abstract

The ability to predict tourist movements has various practical applications, including recommendation, target marketing, and destination planning. Predictability determines the limit of the prediction accuracy of data and models and helps us understand the factors affecting the prediction accuracy. We first constructed a conceptual framework of factors influencing the predictability from three perspectives: tourist, destination, and space-time. In this study, we focused on factors affecting the tourist movement predictability using data collected from social media at the city level. We used two prediction models to understand the impact of the factors on predictability. We further analyzed the relationship between the factors and movement predictability. The results of this study demonstrate that the length of the tourist itinerary and the spatial scale of the study are key factors that influence model selection. In addition, the results indicate significant differences in the predictability of tourists with different tourism motivations.