A Visual Analytics Framework for Microblog Data Analysis at Multiple Scales of Aggregation

• Published in: Computer graphics forum Vol. 35; no. 3; pp. 441 - 450
• Main Authors: Zhang, Jiawei, Ahlbrand, Benjamin, Malik, Abish, Chae, Junghoon, Min, Zhiyu, Ko, Sungahn, Ebert, David S.
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.06.2016
• Subjects: Analysis; Analytics; Blogs; Categories; Categories and Subject Descriptors (according to ACM CCS); Computer graphics; Datasets; Decision making; Disaster Management; Disasters; Emergency preparedness; Exploration; I.3.3 [Computer Graphics]: Visual Analytics; I.3.3 [Computer Graphics]: Visual Analytics, Social Media Analysis, Disaster Management; Real time; Situational awareness; Social Media Analysis; Social networks; Studies; Visual; Visualization
• ISSN: 0167-7055; 1467-8659
• DOI: 10.1111/cgf.12920

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.