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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/sa5vr5kjjfdcbdb5uixas6o3i4" style="color: black;">Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies</a>
We present the first large-scale analysis of POI revisitation patterns, which aims to model the periodic behavior in human mobility. We apply the revisitation analysis technique, which has previously been used to understand website revisitation, and smartphone app revisitations. We analyze a 1.5-year-long Foursquare check-in dataset with 266,909 users in 415 cities around the globe, as well as a Chinese social networking dataset on continuous localization of 15,000 users in Beijing. Our<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3287034">doi:10.1145/3287034</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bmhbpjxdlrbjphrfqncssfwrkm">fatcat:bmhbpjxdlrbjphrfqncssfwrkm</a> </span>
more »... identifies four major POI revisitation patterns and four user revisitation patterns of distinct characteristics, and demonstrates the role of POI functions and geographic constraints in shaping these patterns. We compare our results to previous analysis on website and app revisitation, and highlight the similarities and differences between physical and cyber revisitation activities. These point to fundamental characteristics of human behavior.
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