Cross-Domain Analysis of the Blogosphere for Trend Prediction

  • Patrick SiehndelEmail author
  • Fabian Abel
  • Ernesto Diaz-Aviles
  • Nicola Henze
  • Daniel Krause
Part of the Lecture Notes in Social Networks book series (LNSN, volume 6)


In the recent years blogs became an important part of the web. New technologies like smartphones emerged that enable blogging at any time and make blogs more up-to-date than ever before. Due to their high popularity they are a valuable source of information regarding public opinions about all kind of topics. Blog postings that refer to products are of particular interest for companies to adjust marketing campaigns or advertisement. In this article we compare the blogging characteristics of two different domains: the music and the movie domain. We investigate how chatter from the blogosphere can be used to predict the success of products. We analyze and identify typical patterns of blogging behavior around the release of a product, point out methods for extracting features from the blogosphere and show that we can exploit these features to predict the monetary success of movies and music with high accuracy.


Sales Performance Trend Prediction Movie Title Movie Product Music Domain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Wien 2013

Authors and Affiliations

  • Patrick Siehndel
    • 1
    Email author
  • Fabian Abel
    • 2
  • Ernesto Diaz-Aviles
    • 1
  • Nicola Henze
    • 1
  • Daniel Krause
    • 1
  1. 1.L3S Research CenterLeibniz University HannoverHannoverGermany
  2. 2.Web Information SystemsDelft University of TechnologyDelftThe Netherlands

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