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Checking in or checked in: comparing large-scale manual and automatic location disclosure patterns

Published: 04 December 2012 Publication History

Abstract

Studies on human mobility are built on two fundamentally different data sources: manual check-in data that originates from location-based social networks and automatic check-in data that can be automatically collected through various smartphone sensors. In this paper, we analyze the differences and similarities of manual check-ins from Foursquare and automatic check-ins from Nokia's Mobile Data Challenge. Several new findings follow from our analysis: (1) While automatic checking-in overall results in more visits than manual checking-in, the check-in levels are comparable when visiting new places. (2) Daily and weekly check-in activity patterns are similar for both systems except for Saturdays -- when manual check-ins are relatively more probable. (3) A recently proposed rank distribution to describe human mobility, so far validated on manual check-in data, also holds for automatic check-in data given a slight modification to the definition of rank. (4) The patterns described by automatic check-ins are in general more predictable. We also address the question of whether it is possible to find matching places across the two check-in systems. Our analysis shows that while this is challenging in areas such as city centers, our method achieves an accuracy of 51% for places that are not homes of phone users.

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  1. Checking in or checked in: comparing large-scale manual and automatic location disclosure patterns

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      cover image ACM Other conferences
      MUM '12: Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia
      December 2012
      383 pages
      ISBN:9781450318150
      DOI:10.1145/2406367
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      Published: 04 December 2012

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      Author Tags

      1. MDC
      2. check-ins
      3. foursquare
      4. place matching

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      • (2020)Robot-Centric Perception of Human GroupsACM Transactions on Human-Robot Interaction10.1145/33757989:3(1-21)Online publication date: 31-May-2020
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