Filippo Radicchi Graph-based ranking algorithms BioCenit Research - - PowerPoint PPT Presentation

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Filippo Radicchi Graph-based ranking algorithms BioCenit Research - - PowerPoint PPT Presentation

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Filippo Radicchi Graph-based ranking algorithms BioCenit Research Lab @ Universitat Rovira i Virgili Why analyze bibliographic data? Scientif i c motivation Electronic databases store a huge amount of information about scientif i c

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Filippo Radicchi

BioCenit Research Lab @ Universitat Rovira i Virgili

Graph-based ranking algorithms

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Collaboration networks Collaboration networks Citation networks Citation networks

Scientif i c motivation

Electronic databases store a huge amount of information about scientif i c publications ( only in 2006, Journals ~104 Papers ~106 Citations ~107 )

Why analyze bibliographic data?

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Practical motivation

Citations represent the fundamental units used to measure the scientif i c relevance of papers, journals, scientists, research groups and institutions

Why analyze bibliographic data?

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Discipline Discipline Researcher Researcher

  • Ass. Professor
  • Ass. Professor

Full Professor Full Professor Mathematics Mathematics Physics Physics Biology Biology

Computer Sci Computer Sci. .

source: ”Indicatori di Attività Scientif i ca e di Ricerca”, Consiglio Universitario Nazionale (CUN), Dec. 2008

P = # publications, T = period of activity , C = total # of citations

Chemistry Chemistry

A practical example

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A practical example

source: ”Abilitazione Scientif i ca Nazionale – La normalizzazione degli indicatori per l'eta' accademica (ANVUR)”, Jul. 2012

1) Number of papers:

2) Total number of citations: I ( N p , AA)=10 N p A A I ( N C , AA)= N C AA

3) Contemporary h-index: S (i ,t i ,t)=

4 (t−ti+1) C (i ,t i ,t)

AA N p N C C(i ,t i ,t)

hc

total number of papers academic age total number of citations

citations accumulated by paper i published in year ti and measured in year t

  • A. Sidiropoulos et al., Scientometrics 72, 253 (2007)
  • R. Manella and P. Rossi, arXiv:1207.3499 (2012)

calculated over a population of 1400 Italian physicists

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On a larger sample of scientists

35000 prof i les on Google Scholar citations

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The network structure of citation data is often neglected in research evaluation

D.J. de Solla Price, Science 169, 510 (1965)

Network approach Network approach “ “Standard” approach Standard” approach

Citation counts Citation counts h-index, g-index, ... h-index, g-index, ... Impact factor Impact factor

papers journals scientists

CiteRank CiteRank Eigenfactor Eigenfactor

? ?

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Physical Review Series I (PRI), Physical Review (PR), Physical Review Letters (PRL), Physical Review A (PRA), Physical Review B (PRB), Physical Review C (PRC), Physical Review D (PRD), Physical Review E (PRE), Reviews of Modern Physics (RMP)

between 1893 and 2006

Paper Citation Network Paper Citation Network Weighted Author Citation Network Weighted Author Citation Network

Graph-based ranking of scientists

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key-words: ”complex network” , ”scale-free network”, ”small-world network”, etc..

Weighted author citation network

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Divide 8,783,994 total references into Divide 8,783,994 total references into homogeneous homogeneous intervals intervals

M MI

I = # of intervals

= # of intervals M MR

R = # of references in each interval

= # of references in each interval

M MR

R

2M 2MR

R

M MI

I M

MR

R

(M (MI

I-1)

  • 1)

M

MR

R

(M (MI

I-2)

  • 2)

M

MR

R

MR/2 3MR/2

(MI - 1/2) MR (MI - 3/2) MR

MR ~ 488,000 MI = 18 2006 1893-1966

Dynamical representation

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Diffusion equation

weight of the arc from j to i

  • ut-strength of the node j

each paper carries a ”scientif i c credit”, equally divided among its authors

SARA scores depend on the choice of the redistribution probability q

Science Author Rank Algorithm

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Science Author Rank Algorithm

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Benchmarking SARA

Considered prizes: Nobel prize, Wolf prize, Boltzmann medal, Dirac medal and Planck medal

Comparison with different metrics

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NP= Nobel prize, WP= Wolf prize, BM= Boltzmann medal, DM= Dirac medal, and PM= Planck medal

Best physicists according to SARA

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physauthorsrank.org

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Ranking tennis players

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ATP points distribution as of 2009

Grand Slams: Australian Open, Roland Garros, Wimbledon, US Open Masters 1000: Indian Wells, Miami, Monte Carlo, Madrid, Rome, Canada, Cincinnati, Shanghai, Paris 500 Series: Rotterdam, Memphis, Acapulco, Dubai, Barcelona, Hamburg, Washington, Beijing, Tokyo, Basel, Valencia 250 Series: Doha, Chennai, Brisbane, Sydney, Auckland, ........

4 9 11 40

Best results in 18 tournaments: 4 Grand Slams, 8 Masters 1000, best 4 results in 500 Series and best 2 results in 250 Series

source: wikipedia.org

ATP World Tour Finals: reserved to the best 8 players in the ranking

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ATP points 2008 ATP points 2009

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ATP data cover all tournaments since 1968

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The Open Era

3700 players, 3600 tournaments, 133000 matches

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Tennis contact graph

each match is a directed edge from the loser to the winner edges are weighted wi , j = total matches i vs. j, won by j

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Top players in Grand Slams

Only players with at least two Grand Slam titles between 1968 and 2010

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Tennis is “complex”

Matthew effect in career longevity, A.M. Pertersen at al., Proc. Natl. Acad. Sci. USA 108, 18 (2011)

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Prestige score

diffusion random relocation

correction for dangling nodes

for a Grand Slam tournament for a tournament

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#3 : John McEnroe

Career prize money: $12,547,797 Career record: 875–198 (81.55%) Career titles: 104 including 77 listed by the ATP

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#2 : Ivan Lendl

Career prize money: $21,262,417 Career record: 1071–239 (81.8%) Career titles: 144 including 94 listed by the ATP

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#1 : Jimmy Connors

Career prize money: $8,641,040 Career record: 1241–277 (81.75%) Career titles: 148 including 109 listed by the ATP

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Prestige Rank

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Relation with other scores

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Relation with other scores

2009 ATP year-end rank

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Best player of the year

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Best player of the year

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Best players in Grand Slams

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What did people think about this ranking?

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What did players think about this ranking?

journalist: “There is a weird study by an American physician...” Pete: “Who is this guy!?!?!?!”

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References

  • F. Radicchi

PloS ONE 6, e17249 (2011)

  • F. Radicchi, S. Fortunato, B. Markines and A. Vespignani
  • Phys. Rev. E 80, 056103 (2009)

Diffusion of scientif i c credits and the ranking of scientists Who is the best player ever? A complex network analysis of the history of professional tennis

  • F. Radicchi, S. Fortunato and A. Vespignani

In Models of Science Dynamics: Encounters Between Complexity Theory and Information Sciences.

  • Eds. A.Scharnhorst; K. Börner and P. van den Besselaar (Springer, 2012)

Citation networks

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Can bibliographic data be used for research evaluation?

discipline discipline scientist scientist h-index h-index

Physics

Edward Witten Marvin Cohen Philip W. Anderson Manuel Cardona Frank Wilczek 110 94 91 86 68

Chemistry

George Whitesides Martin Karplus Kurt Wuthrich 135 Elias J. Corey Alan Hegeer 132 129 114 113

Computer science

Hector Garcia- Molina Ian Foster 70 Deborah Estrin Scott Shenker, Jeffrey D. Ullman, Don Towsley 68 67 65

  • P. Ball, Nature 448, 737 (2007)
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Papers are classified in 172 scientific disciplines (from A

c

  • u

s t i c s to Z

  • l
  • g

y ) Publication year Publication year Number of citations Number of citations

Papers Papers Journals Journals Subject Categories Subject Categories

Description of the dataset

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Source of data March 2008

Different scientific disciplines

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Different scientific disciplines

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Different scientific disciplines