Interactive Visual Discovering of Movement Patterns from Sparsely Sampled Geo-tagged Social Media Data

Social media data with geotags can be used to track people's movements in their daily lives. By providing both rich text and movement information, visual analysis on social media data can be both interesting and challenging. In contrast to traditional movement data, the sparseness and irregular...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1998. - 22(2016), 1 vom: 01. Jan., Seite 270-9
1. Verfasser: Chen, Siming (VerfasserIn)
Weitere Verfasser: Yuan, Xiaoru, Wang, Zhenhuang, Guo, Cong, Liang, Jie, Wang, Zuchao, Zhang, Xiaolong Luke, Zhang, Jiawan
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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520 |a Social media data with geotags can be used to track people's movements in their daily lives. By providing both rich text and movement information, visual analysis on social media data can be both interesting and challenging. In contrast to traditional movement data, the sparseness and irregularity of social media data increase the difficulty of extracting movement patterns. To facilitate the understanding of people's movements, we present an interactive visual analytics system to support the exploration of sparsely sampled trajectory data from social media. We propose a heuristic model to reduce the uncertainty caused by the nature of social media data. In the proposed system, users can filter and select reliable data from each derived movement category, based on the guidance of uncertainty model and interactive selection tools. By iteratively analyzing filtered movements, users can explore the semantics of movements, including the transportation methods, frequent visiting sequences and keyword descriptions. We provide two cases to demonstrate how our system can help users to explore the movement patterns 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
700 1 |a Yuan, Xiaoru  |e verfasserin  |4 aut 
700 1 |a Wang, Zhenhuang  |e verfasserin  |4 aut 
700 1 |a Guo, Cong  |e verfasserin  |4 aut 
700 1 |a Liang, Jie  |e verfasserin  |4 aut 
700 1 |a Wang, Zuchao  |e verfasserin  |4 aut 
700 1 |a Zhang, Xiaolong Luke  |e verfasserin  |4 aut 
700 1 |a Zhang, Jiawan  |e verfasserin  |4 aut 
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