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International Workshop on Algorithms and Models for the Web-Graph

WAW 2010: Algorithms and Models for the Web-Graph pp 50–61Cite as

Modeling Traffic on the Web Graph

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6516))

Abstract

Analysis of aggregate and individual Web requests shows that PageRank is a poor predictor of traffic. We use empirical data to characterize properties of Web traffic not reproduced by Markovian models, including both aggregate statistics such as page and link traffic, and individual statistics such as entropy and session size. As no current model reconciles all of these observations, we present an agent-based model that explains them through realistic browsing behaviors: (1) revisiting bookmarked pages; (2) backtracking; and (3) seeking out novel pages of topical interest. The resulting model can reproduce the behaviors we observe in empirical data, especially heterogeneous session lengths, reconciling the narrowly focused browsing patterns of individual users with the extreme variance in aggregate traffic measurements. We can thereby identify a few salient features that are necessary and sufficient to interpret Web traffic data. Beyond the descriptive and explanatory power of our model, these results may lead to improvements in Web applications such as search and crawling.

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Author information

Authors and Affiliations

  1. School of Informatics and Computing, Indiana University, Bloomington, USA

    Mark R. Meiss, Bruno Gonçalves, Alessandro Flammini & Filippo Menczer

  2. Center for Complex Networks and Systems Research, Indiana University, Bloomington, USA

    Bruno Gonçalves, Alessandro Flammini & Filippo Menczer

  3. Pervasive Technology Institute, Indiana University, Bloomington, USA

    Mark R. Meiss, Bruno Gonçalves & Filippo Menczer

  4. Complex Networks and Systems Lagrange Laboratory, ISI Foundation, Turin, Italy

    José J. Ramasco & Filippo Menczer

Authors
  1. Mark R. Meiss
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  2. Bruno Gonçalves
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  3. José J. Ramasco
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  4. Alessandro Flammini
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  5. Filippo Menczer
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Editor information

Editors and Affiliations

  1. Yahoo! Research, 701 First Ave., 94089, Sunnyvale, CA, USA

    Ravi Kumar

  2. Google Research, 1600 Amphitheatre Parkway, 94043, Mountain View, CA, USA

    Dandapani Sivakumar

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© 2010 Springer-Verlag Berlin Heidelberg

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Meiss, M.R., Gonçalves, B., Ramasco, J.J., Flammini, A., Menczer, F. (2010). Modeling Traffic on the Web Graph. In: Kumar, R., Sivakumar, D. (eds) Algorithms and Models for the Web-Graph. WAW 2010. Lecture Notes in Computer Science, vol 6516. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18009-5_6

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  • DOI: https://doi.org/10.1007/978-3-642-18009-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-18008-8

  • Online ISBN: 978-3-642-18009-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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