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The Influence of Technology on Social Network Analysis and Mining pp 275–301Cite as

Cross-Domain Analysis of the Blogosphere for Trend Prediction

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Part of the book series: Lecture Notes in Social Networks ((LNSN,volume 6))

Abstract

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.

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Notes

  1. 1.

    http://blogpulse.com

  2. 2.

    http://www.blogscope.net/

  3. 3.

    http://twitter.com

  4. 4.

    http://search.twitter.com

  5. 5.

    http://www.amazon.com/gp/help/customer/display.html?nodeId=525376

  6. 6.

    http://boxofficemojo.com/

  7. 7.

    http://lucene.apache.org/java/2_4_0/scoring.html

  8. 8.

    http://blog.spinn3r.com/2007/10/announcing-spin.html

  9. 9.

    http://www.spinn3r.com/

  10. 10.

    http://lucene.apache.org/

  11. 11.

    http://www.cs.waikato.ac.nz/ml/weka/

  12. 12.

    http://www.imdb.com

  13. 13.

    http://swn.isti.cnr.it/

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Author information

Authors and Affiliations

  1. L3S Research Center, Leibniz University Hannover, Appelstr. 4, 30167, Hannover, Germany

    Patrick Siehndel, Ernesto Diaz-Aviles, Nicola Henze & Daniel Krause

  2. Web Information Systems, Delft University of Technology, Mekelweg 4, 2628, Delft, The Netherlands

    Fabian Abel

Authors
  1. Patrick Siehndel
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  2. Fabian Abel
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  3. Ernesto Diaz-Aviles
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  4. Nicola Henze
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  5. Daniel Krause
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Corresponding author

Correspondence to Patrick Siehndel .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, TOBB University, Sogutozu Cad No. 43, Sogutozu Ankara, Turkey

    Tansel Özyer

  2. Computer Science, University of Calgary, University Dr. NW 2500, Calgary, T2N 1N4, Canada

    Jon Rokne

  3. IPSC, European Commission Joint Research Cent., Via Enrico Fermi 2749, Ispra, 21027, Italy

    Gerhard Wagner

  4. De Wetstraat 16, Leiden, 2332 XT, Netherlands

    Arno H.P. Reuser

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Siehndel, P., Abel, F., Diaz-Aviles, E., Henze, N., Krause, D. (2013). Cross-Domain Analysis of the Blogosphere for Trend Prediction. In: Özyer, T., Rokne, J., Wagner, G., Reuser, A. (eds) The Influence of Technology on Social Network Analysis and Mining. Lecture Notes in Social Networks, vol 6. Springer, Vienna. https://doi.org/10.1007/978-3-7091-1346-2_12

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  • DOI: https://doi.org/10.1007/978-3-7091-1346-2_12

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  • Online ISBN: 978-3-7091-1346-2

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