Paper Info
Title
Sci-Fin: Visual Mining Spatial and Temporal Behavior Features from Social Media.
Abstract
Check-in records are usually available in social services, which offer us the opportunity to capture and analyze users' spatial and temporal behaviors. Mining such behavior features is essential to social analysis and business intelligence. However, the complexity and incompleteness of check-in records bring challenges to achieve such a task. Different from the previous work on social behavior analysis, in this paper, we present a visual analytics system, Social Check-in Fingerprinting (Sci-Fin), to facilitate the analysis and visualization of social check-in data. We focus on three major components of user check-in data: location, activity, and profile. Visual fingerprints for location, activity, and profile are designed to intuitively represent the high-dimensional attributes. To visually mine and demonstrate the behavior features, we integrate WorldMapper and Voronoi Treemap into our glyph-like designs. Such visual fingerprint designs offer us the opportunity to summarize the interesting features and patterns from different check-in locations, activities and users (groups). We demonstrate the effectiveness and usability of our system by conducting extensive case studies on real check-in data collected from a popular microblogging service. Interesting findings are reported and discussed at last.
Year
DOI
Venue
2016
10.3390/s16122194
SENSORS
Keywords
Field
DocType
visual mining,big data analysis,spatial and temporal behaviors,social media,Internet of things
Data science,World Wide Web,Social media,Visualization,Usability,Microblogging,Visual analytics,Electronic engineering,Voronoi diagram,Engineering,Business intelligence,Big data
Journal
Volume
Issue
ISSN
16
12
1424-8220
Citations 
PageRank 
References 
1
0.37
4
Authors
5
Name
Order
Citations
PageRank
Jiansu Pu122.77
Zhiyao Teng210.37
Rui Gong310.37
Changjiang Wen410.37
Yang Xu563.23