Name
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2535771.2535786 | HotNets |
Keywords | Field | DocType |
extraneous checkins,large ground truth dataset,geosocial mobility trace,geosocial datasets,checkin event,foursquare checkin trace,missing checkins,gps trace,large portion,foursquare checkins,measurement,mobility | Data science,Computer science,Computer security,Correctness,Computer network,Ground truth,Global Positioning System | Conference |
Citations | PageRank | References |
15 | 0.74 | 26 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zengbin Zhang | 1 | 536 | 27.05 |
| Lin Zhou | 2 | 15 | 0.74 |
| Xiaohan Zhao | 3 | 237 | 10.45 |
| Gang Wang | 4 | 465 | 25.30 |
| Yu Su | 5 | 771 | 34.45 |
| Miriam Metzger | 6 | 15 | 0.74 |
| Haitao Zheng | 7 | 1073 | 70.54 |
| Ben Y. Zhao | 8 | 6274 | 490.12 |