On the validity of geosocial mobility traces
Abstract
Mobile networking researchers have long searched for large-scale, fine-grained traces of human movement, which have remained elusive for both privacy and logistical reasons. Recently, researchers have begun to focus on geosocial mobility traces, e.g. Foursquare checkin traces, because of their availability and scale. But are we conceding correctness in our zeal for data? In this paper, we take initial steps towards quantifying the value of geosocial datasets using a large ground truth dataset gathered from a user study. By comparing GPS traces against Foursquare checkins, we find that a large portion of visited locations is missing from checkins, and most checkin events are either forged or superfluous events. We characterize extraneous checkins, describe possible techniques for their detection, and show that both extraneous and missing checkins introduce significant errors into applications driven by these traces.
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About 75% of Foursquare check-ins do not match users' real mobility, influenced by Foursquare's competitive game-like mechanisms.
“Zhang et al. (2013) found that about 75% of Foursquare check-ins do not match users' real mobility, being influenced by Foursquare's competitive game-like mechanisms”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Zhang et al., 2013
Cites
Limits of Predictability in Human Mobility
Song, C., Qu, Z., Blumm, N., & Barabási, A.-L. (2010) · Science · doi:10.1126/science.1177170 · Cited by 3,234 · see citing works
Exploiting place features in link prediction on location-based social networks
Scellato, S., Noulas, A., & Mascolo, C. (2011) · Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/2020408.2020575 · Cited by 522 · see citing works
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Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kıcıman, E. (2019) · Frontiers in Big Data · doi:10.3389/fdata.2019.00013 · Cited by 763 · see citing works
Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kiciman, E. (2016) · doi:10.2139/ssrn.2886526 · Cited by 763 · see citing works
- Authors
- Zhang, Z., Zhou, L., Zhao, X., Wang, G., Su, Y., Metzger, M., Zheng, H., & Zhao, B. Y.
- Affiliations
- University of California, Santa Barbara (US)
- UC Santa Barbara, Santa Barbara, CA
- Venue
- Proceedings of the Twelfth ACM Workshop on Hot Topics in Networks
- Publisher
- ACM
- Published
- 2013-11-21
- Pages
- 1-7
- OpenAlex
- W2103033197
- Cited by
- 52
- References
- 2
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 1 · 2022: 3 · 2021: 8 · 2020: 6 · 2019: 6 · 2018: 7 · 2017: 3 · 2016: 7 · 2015: 3 · 2014: 4
- FWCI
- 6.41
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Workshop on Hot Topics in Networks (HotNets) (publishedVersion)
- Topics
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Physical Sciences › Computer Science › Signal Processing › Data Management and Algorithms
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- GPS tracks, data quality, data falsification, human mobility, ground truth dataset, user study, location-based services
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