Paper Info
Title
TravelDiff: Visual comparison analytics for massive movement patterns derived from Twitter
Abstract
Geo-tagged microblog data covers billions of movement patterns on a global and local scale. Understanding these patterns could guide urban and traffic planning or help coping with disaster situations. We present a visual analytics system to investigate travel trajectories of people reconstructed from microblog messages. To analyze seasonal changes and events and to validate movement patterns against other data sources, we contribute highly interactive visual comparison methods that normalize and contrast trajectories as well as density maps within a single view. We also compute an adaptive hierarchical graph from the trajectories to abstract individual movements into higher-level structures. Specific challenges that we tackle are, among others, the spatio-temporal sparsity of the data, the volume of data varying by region, and a diverse mix of means of transportation. The applicability of our approach is presented in three case studies.
Year
DOI
Venue
2016
10.1109/PACIFICVIS.2016.7465266
2016 IEEE Pacific Visualization Symposium (PacificVis)
Keywords
Field
DocType
TravelDiff,visual comparison analytics,massive movement pattern,Twitter,geo-tagged microblog data,urban planning,traffic planning,visual analytics system,travel trajectory,interactive visual comparison method,density maps,adaptive hierarchical graph,spatio-temporal sparsity
Data science,Graph,Visual comparison,Social media,Normalization (statistics),Local scale,Computer science,Microblogging,Visual analytics,Interactive visual analysis,Analytics
Conference
ISSN
Citations 
PageRank 
2165-8765
7
0.44
References 
Authors
34
5
Name
Order
Citations
PageRank
Robert Krueger1282.47
Guo-Dao Sun217111.24
Fabian Beck359143.93
Ronghua Liang437642.60
Thomas Ertl54417401.52