Black swan: augmenting statistics with event data

  • Authors:

  • Johannes Lorey;Felix Naumann;Benedikt Forchhammer;Andrina Mascher;Peter Retzlaff;Armin ZamaniFarahani;Soeren Discher;Cindy Faehnrich;Stefan Lemme;Thorsten Papenbrock;Robert Christoph Peschel;Stephan Richter;Thomas Stening;Sven Viehmeier

  • Affiliations:

  • Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany;Hasso Plattner Institute, Potsdam, Germany

  • Venue:
  • Proceedings of the 20th ACM international conference on Information and knowledge management
  • Year:
  • 2011

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Abstract

A large number of statistical indicators (GDP, life expectancy, income, etc.) collected over long periods of time as well as data on historical events (wars, earthquakes, elections, etc.) are published on the World Wide Web. By augmenting statistical outliers with relevant historical occurrences, we provide a means to observe (and predict) the influence and impact of events. The vast amount and size of available data sets enable the detection of recurring connections between classes of events and statistical outliers with the help of association rule mining. The results of this analysis are published at http://www.blackswanevents.org and can be explored interactively.