Visualizing Contextual and Dynamic Features of Micropost Streams

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 highvolume 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 multidimensional 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 micropost streams through dynamic topography information landscapes, news flow diagrams and longitudinal cross-media analyses.