RendezView: An Interactive Visual Mining Tool for Discerning Flock Relationships in Social Media Data
Authors: Melissa J. Bica (University of Colorado Boulder), Kyoung-Sook Kim (National Institute of Advanced Industrial Science and Technology)
Abstract: Social media data provide insight into people's opinions, thoughts, and reactions about real-world events. However, this data is often analyzed at a shallow level with simple visual representations, making much of this insight indiscoverable. Our approach to this problem was to create a framework for visual data mining that enables users to find implicit patterns and relationships within their data, focusing particularly on flock phenomena in social media. RendezView is an interactive visualization framework consisting of three visual components: a spatiotemporal 3D map, a word cloud, and a Sankey flow diagram. These provide individual functions for data exploration and interoperate with each other based on user interaction. The current version of RendezView can represent local topics and their co-occurrence relationships from geo-tagged Twitter messages. This work will be presented by focusing on visualizations, information representation, and interactions, and a live demo will be available to show the system in use.
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