Abstract

In this work, we discuss how an existing algorithm to extract long-distance trips from mobile phone data (Janzen et al., 2016 a,b) can be supplemented with man-made heuristics to arrive at plausible domestic tourism trips. In total, we detect 18,380 domestic tourism trips from mobile phone data of 69,000 users sampled in 32 cities in France. By analysing temporal, spatial and social characteristics of the domestic tourism trips, we explore several possible directions for the use of mobile phone data when studying domestic tourism on a large scale. We show how temporal patterns of mobile phone use differ from baseline behaviour, how destinations of trips can algorithmically be derived, and how future research can integrate information on the activation of the social network. Our main contribution is that we describe current barriers and sketch direction for future research.

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