Visualizing contextual and dynamic features of micropost streams

  • Hubmann-Haidvogel A
  • Braşoveanu A
  • Scharl A
 et al. 
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Visual techniques provide an intuitive way of making sense of the large amounts of microposts available from social media sources, particularly in the case of emerging topics of interest to a global audience, which often raise controversy among key stakeholders. Micropost streams are context-dependent and highly dynamic in nature. We describe a visual analytics platform to handle high-volume micropost streams from multiple social media channels. For each post we extract key contextual features such as location, topic and sentiment, and subsequently render the resulting multi-dimensional information space using a suite of coordinated views that support a variety of complex information seeking behaviors. We also describe three new visualization techniques that extend the original platform to account for the dynamic nature of micro¬post streams through dynamic topography information landscapes, news flow diagrams and longitudinal cross-media analyses.

Author-supplied keywords

  • Contextual features
  • Dynamic visualization
  • Information landscape
  • Microposts
  • News flow
  • Social media analytics

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  • PUI: 372090598
  • SGR: 84891924352
  • SCOPUS: 2-s2.0-84891924352
  • ISSN: 16130073


  • Arno ScharlwebLyzard technology

  • Alexander Hubmann-Haidvogel

  • Adrian M.P. Braşoveanu

  • Marta Sabou

  • Stefan Gindl

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