
doi: 10.1109/mc.2012.430
The application of visual analytics, which combines the advantages of computational knowledge discovery and interactive visualization, to social media data highlights the many benefits of this integrated approach. The Web extra at http://youtu.be/nhoq71gqyXE is a video demonstrating a prototype system for visual-interactive analysis of large georeferenced microblog datasets, describing the design of the system, and detailing its application to the VAST 2011 Challenge dataset. The dataset models an epidemic outbreak in a fictitious metropolitan area. The video shows how the system can detect the epidemic and analyze its development over time. The system was implemented by Juri Buchmueller, Fabian Maass, Stephan Sellien, Florian Stoffel, and Matthias Zieker at the University of Konstanz (they also produced this video). Further information on the system and the VAST challenge dataset can be found in E. Bertini et al., "Visual Analytics of Terrorist Activities Related to Epidemics," Proc. IEEE Conf. Visual Analytics Science and Technology (VAST 11), IEEE CS, pp. 329-330, 2011.
info:eu-repo/classification/ddc/004
info:eu-repo/classification/ddc/004
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| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
