E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media


Significant events are often discussed and spread through social media, involving many people. Reposting activities and opinions expressed in social media offer good opportunities to understand the evolution of events. However, the dynamics of reposting activities and the diversity of user comments pose challenges to understand event-related social media data. We propose E-Map, a visual analytics approach that uses map-like visualization tools to help multi-faceted analysis of social media data on a significant event and in-depth understanding of the development of the event. E-Map transforms extracted keywords, messages, and reposting behaviors into map features such as cities, towns, and rivers to build a structured and semantic space for users to explore. It also visualizes complex posting and reposting behaviors as simple trajectories and connections that can be easily followed. By supporting multi-level spatial temporal exploration, E-Map helps to reveal the patterns of event development and key players in an event, disclosing the ways they shape and affect the development of the event. Two cases analysing real-world events confirm the capacities of E-Map in facilitating the analysis of event evolution with social media data.


Siming Chen, Shuai Chen, Lijing Lin, Xiaoru Yuan, Jie Liang and Xiaolong (Luke) Zhang.
E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media.
In Proceedings of IEEE Conference on Visual Analytics Science and Technology (VAST'17), Phoenix, USA, Oct. 1-6, 2017.


Spatial temporal visual analytics system of E-Map








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