Paper Info
Title
MovementFinder: Visual analytics of origin-destination patterns from geo-tagged social media
Abstract
Geo-tagged social media data can be viewed as sampling of people's trajectories in daily life. It consists of people's movements and embeds the semantics of movements. However, it is challenging to reveal patterns from the sparse and irregular sampling data. We proposed an interactive multi-filter visualization approach to analyze the spatial-temporal movement pattern in people's daily life. People's trajectories are visualized on the map with multiple functional layers. With our visual analytics tools, users are able to drill down to details, with the awareness of the origin-destination flow patterns of spatial, temporal, and semantic meaning.
Year
DOI
Venue
2014
10.1109/VAST.2014.7042509
IEEE VAST
Keywords
Field
DocType
movementfinder,people trajectory visualization,spatial-temporal movement pattern analysis,people trajectory sampling,movement semantics,functional layers,origin-destination flow patterns,geography,information filters,data visualisation,visual analytics,people movements,geo-tagged social media,social networking (online),interactive multifilter visualization approach
Data mining,Social media,Visualization,Computer science,Visual analytics,Drill down,Sampling (statistics),Semantics
Conference
ISSN
Citations 
PageRank 
2325-9442
2
0.36
References 
Authors
5
5
Name
Order
Citations
PageRank
Siming Chen112514.34
Cong Guo21005.18
Xiaoru Yuan3115770.28
Zhang Jiawan436946.66
Xiaolong Luke Zhang530.78