A Visual Analytics Framework for Microblog Data Analysis at Multiple Scales of Aggregation. (4th July 2016)

• Record Type: Journal Article
• Authors: Zhang, Jiawei; Ahlbrand, Benjamin; Malik, Abish; Chae, Junghoon; Min, Zhiyu; Ko, Sungahn; Ebert, David S.
• Is Part Of: Computer graphics forum. Volume 35:Number 3(2016)
• Page Start: 441
• Page End: 450
• Publication Date: 2016-07-04
• Subjects: Categories and Subject Descriptors (according to ACM CCS): -- I.3.3 [Computer Graphics]: Visual Analytics, Social Media Analysis, Disaster Management—; Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.12920
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract: Real‐time microblogs can be utilized to provide situational awareness during emergency and disaster events. However, the utilization of these datasets requires the decision makers to perform their exploration and analysis across a range of data scales from local to global, while maintaining a cohesive thematic context of the transition between the different granularity levels. The exploration of different information dimensions at the varied data and human scales remains to be a non‐trivial task. To this end, we present a visual analytics situational awareness environment that supports the real‐time exploration of microblog data across multiple scales of analysis. We classify microblogs based on a fine‐grained, crisis‐related categorization approach, and visualize the spatiotemporal evolution of multiple categories by coupling a spatial lens with a glyph‐based visual design. We propose a transparency‐based spatial context preserving technique that maintains a smooth transition between different spatial scales. To evaluate our system, we conduct user studies and provide domain expert feedback.