[tt] How Google's PageRank predicts Nobel Prize winners

[Eugen Leitl]

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From: the physics arXiv blog <howdy at arxivblog.com>
Date: Wed, 21 Jan 2009 13:20:40 +0000
To: eugen at leitl.org
Subject: the physics arXiv blog


[1]the physics arXiv blog

   [2]How Google's PageRank predicts Nobel Prize winners

   Posted: 21 Jan 2009 04:38 AM PST

   pagerankings-graph

   Ranking scientists by their citations-the number of times they are
   mentioned in other scientists' papers- is a miserable business.
   Everybody can point to ways in which this system is flawed:
     * not all citations are equal. The importance of the citing paper is
       a significant factor

     * scientists in different fields of study use citations in different
       ways. An average paper in the life sciences is cited about six
       times, three times in physics, and about once in mathematics.

     * ground-breaking papers may be cited less often because a field is
       necessarily smaller in its early days.

     * important papers often stop being cited when they are incorporated
       into textbooks

   The pattern of citations between papers forms a complex network, not
   unlike the one the internet forms. Might that be a clue that point us
   towards a better way of assessing the merits of the papers that it
   consists of?

   Sergei Maslov from Brookhaven National Laboratory in New York state
   and Sidney Redner at Boston University have asked themselves just that
   question and suggest that Google's PageRank algorithm might throw some
   light on the matter.

   In essence, PageRank counts the number of citations a paper receives
   (or the number of links that point to a webpage). The more a paper
   receives, the higher it is ranked. But a citing is also weighted
   according to the ranking of the citing paper. So citations from
   important papers make another paper more important.

   Maslov and Redner have applied the algorithm to 353,268 articles
   published by the American Physical Society since 1893 in journals such
   as Physical Review Letters . And the results are a breath of fresh
   air.

   The top 10 papers by Google Pageranking are:
    1. Unitary Symmetry & Leptonic Decays by Cabibbo
    2. Theory of Superconductivity by Bardeen, Cooper & Schrieffer
    3. Self-Consistent Equations . . . by Kohn & Sham
    4. Inhomogeneous Electron Gas by Hohenberg & Kohn
    5. A Model of Leptons by Weinberg
    6. Crystal Statistics . . . by Onsager
    7. Theory of the Fermi Interaction by Feynman & Gell-Mann
    8. Absence of Diffusion in . . . by Anderson
    9. The Theory of Complex Spectra by Slater
   10. Scaling Theory of Localization by Abrahams, Anderson, et al.

   That's an impressive list, not least because most of these authors are
   Nobel Prize winners. (Curiously the author of the top paper, Nicola
   Cabibbo, is not. That ought to be of interest to the Nobel committee
   who awarded Makoto Kobayashi and Toshihide Maskawa the 2008 Nobel
   Prize for physics for work that was heavily based on Cabibbo's ideas.)

   All of which suggests an idea. Mining the later entries in this list
   might be an good way of predicting future prize winners. So get your
   bets in before the bookies get wind of it.

   Redner and Maslov conclude: "Googles PageRank algorithm and its
   modifications hold great promise for quantifying the impact of
   scientific publications."

   Can't argue with that.

   Ref: [3]arxiv.org/abs/0901.2640: Promise and Pitfalls of Extending
   Googles PageRank Algorithm to Citation Networks

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References

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   3. http://arxiv.org/abs/0901.2640
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Eugen* Leitl <a href="http://leitl.org">leitl</a> http://leitl.org
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