Contingency Wheel: Visual Analysis of Large Contingency Tables

Bilal Alsallakh, Meister Eduard Gröller, Silvia Miksch, Martin Suntinger
Contingency Wheel: Visual Analysis of Large Contingency Tables
[Paper]

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Abstract

We present the Contingency Wheel, a visual method for finding and analyzing associations in a large nm contingency table with m < 100 and n being two to three orders of magnitude larger than m. The method is demonstrated on a large table from the Book-Crossing dataset, which counts the number of ratings each book received from each country. It enables finding books that received a disproportionately high number of ratings from a specific country. It further allows to visually analyze what these books have in common, and with which countries they are also highly associated. Pairs of similar countries can further be identified (in the sense that many books are associated with both countries). Compared with existing visual methods, our approach enables analyzing and gaining insight into larger tables.

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BibTeX

@WorkshopTalk{Groeller_2011_CW,
  title =      "Contingency Wheel: Visual Analysis of Large Contingency
               Tables",
  author =     "Bilal Alsallakh and Meister Eduard Gr{"o}ller and Silvia
               Miksch and Martin Suntinger",
  year =       "2011",
  abstract =   "We present the Contingency Wheel, a visual method for
               finding and analyzing associations in a large nm contingency
               table with m < 100 and n being two to three orders of
               magnitude larger than m. The method is demonstrated on a
               large table from the Book-Crossing dataset, which counts the
               number of ratings each book received from each country. It
               enables finding books that received a disproportionately
               high number of ratings from a specific country. It further
               allows to visually analyze what these books have in common,
               and with which countries they are also highly associated.
               Pairs of similar countries can further be identified (in the
               sense that many books are associated with both countries).
               Compared with existing visual methods, our approach enables
               analyzing and gaining insight into larger tables.",
  month =      may,
  location =   "Bergen, Norway",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2011/Groeller_2011_CW/",
}