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MobilityGraphs: Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering
2016
IEEE Transactions on Visualization and Computer Graphics
Preserved Fulltext
The analysis of mobility data is challenging due to the need to analyze and compare spatial situations (i.e., presence and flows of people at certain time moments) and to gain an understanding of the spatio-temporal ...
Hourly flows of residential Twitter users in Greater London area over a week are spatially and temporally simplified to gain an overview of mobility dynamics. ...
This research has been partially supported by the EU-funded projects GRACeFUL and SoBigData. ...
doi:10.1109/tvcg.2015.2468111
pmid:26529684
fatcat:cvg5itedr5bfxa37zs6vzfxpha
EpiMob: Interactive Visual Analytics of Citywide Human Mobility Restrictions for Epidemic Control
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2007.03180v1 fatcat:ltjkja4mgrfebbfgxjgdtwwkfiOther Versions
Users can conveniently designate the spatial and temporal ranges for different mobility restriction policies. ...
Thus, based on big human mobility data and city POI data, an interactive visual analytics system called Epidemic Mobility (EpiMob) was designed in this study. ...
Mobilitygraphs [44] utilized graph and clustering to visually understand mass mobility dynamics; [13] focused on pattern discovering from geo-tagged social media data; Telcovis [50] explored co-occurrence ...
arXiv:2007.03180v3
fatcat:2q6bmugq4bbqthyajo4ysv7dra