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Adaptive Visualization of Social Media Data for Policy Modeling

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 8887)

Abstract

The visual analysis of social media data emerged a huge number of interactive visual representations that use different characteristics of the data to enable the process of information acquisition. The social data are used in the domain of policy modeling to gather information about citizens’ demands, opinions, and requirements and help to decide about political policies. Although existing systems already provide a huge number of visual analysis tools, the search and exploration paradigm is not really clear. Furthermore, the systems commonly do not provide any kind of human centered adaptation for the different stakeholders involved in the policy making process. In this paper, we introduce a novel approach that investigates the exploration and search paradigm from two different perspectives and enables a visual adaptation to support the exploration and analysis process.

Keywords

Policy Modeling Information Visualization Visual Variable Social Media Data Search Paradigm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Fraunhofer IGDDarmstadtGermany
  2. 2.TU DarmstadtDarmstadtGermany

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