
Human mobility dataset for the ACM SIGSPATIAL GIS CUP 2025: Human Mobility Prediction Challenge https://sigspatial2025.sigspatial.org/giscup/index.html This data contains movement information generated from user location data obtained from LY Corporation smartphone applications. It does not reveal the actual timestamp, latitude, longitude, etc., and does not identify individuals. This data was originally made available only be used for the purpose of participating in the GIS CUP 2025, but we are releasing the full dataset now. When you use this data for publications, analysis, reports, please give us credits by citing the following publication, which is the Data Descriptor of this dataset. Yabe, T., Tsubouchi, K., Shimizu, T., Sekimoto, Y., Sezaki, K., Moro, E., & Pentland, A. (2024). YJMob100K: City-scale and longitudinal dataset of anonymized human mobility trajectories. Scientific Data, 11(1), 397. https://www.nature.com/articles/s41597-024-03237-9
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
