Visualizing Streaming Text Data with Dynamic Maps by Emden Gansner, Yifan Hu, and Stephen North.
The many endless rivers of text now available present a serious challenge in the task of gleaning, analyzing and discovering useful information. In this paper, we describe a methodology for visualizing text streams in real time. The approach automatically groups similar messages into “countries,” with keyword summaries, using semantic analysis, graph clustering and map generation techniques. It handles the need for visual stability across time by dynamic graph layout and Procrustes projection techniques, enhanced with a novel stable component packing algorithm. The result provides a continuous, succinct view of evolving topics of interest. It can be used in passive mode for overviews and situational awareness, or as an interactive data exploration tool. To make these ideas concrete, we describe their application to an online service called TwitterScope.
Or, see: TwitterScope, at http://bit.ly/HA6KIR.
Worth the visit to see the static pics in the paper in action.
Definitely a tool with a future in data exploration.
I know “Procrustes” from the classics so had to look up Procrustes transformation. Which was reported to mean:
A Procrustes transformation is a geometric transformation that involves only translation, rotation, uniform scaling, or a combination of these transformations. Hence, it may change the size, but not the shape of a geometric object.
Sounds like abuse of “Procrustes” because I would think having my limbs cut off would change my shape. 😉
Intrigued by the notion of not changing “…the shape of a geometric object.”
Could we say that adding identifications to a subject representative does not change the subject it identifies?