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Explanations for Rankings

Ranking methods

The following ranking methods are available. Links show the top 5% authors for each ranking method, with additional detail.
  • NbWorks: Number of Works
  • DNbWorks: Number of Distinct Works
  • ScWorks: Number of Distinct Works, Weighted by Simple Impact Factor
  • WScWorks: Number of Distinct Works, Weighted by Recursive Impact Factor
  • ANbWorks: Number of Distinct Works, Weighted by Number of Authors
  • AScWorks: Number of Distinct Works, Weighted by Number of Authors and Simple Impact Factors
  • AWScWorks: Number of Distinct Works, Weighted by Number of Authors and Recursive Impact Factors
  • NbCites: Number of Citations
  • DCites: Number of Citations, Discounted by Citation Age
  • ScCites: Number of Citations, Weighted by Simple Impact Factor
  • DScCites: Number of Citations, Weighted by Simple Impact Factor, Discounted by Citation Age
  • WScCites: Number of Citations, Weighted by Recursive Impact Factor
  • WDScCites: Number of Citations, Weighted by Recursive Impact Factor, Discounted by Citation Age
  • ANbCites: Number of Citations, Weighted by Number of Authors
  • ADCites: Number of Citations, Weighted by Number of Authors, Discounted by Citation Age
  • AScCites: Number of Citations, Weighted by Number of Authors and Simple Impact Factors
  • ADScCites: Number of Citations, Weighted by Number of Authors and Simple Impact Factors, Discounted by Citation Age
  • AWScCites: Number of Citations, Weighted by Number of Authors and Recursive Impact Factors
  • AWDScCites: Number of Citations, Weighted by Number of Authors and Recursive Impact Factors, Discounted by Citation Age
  • HIndex: h, where author has written h papers that have each been cited at least h times
  • NCAuthors: Number of Registered Citing Authors
  • RCAuthors: Number of Registered Citing Authors, Weighted by Rank (Max. 1 per Author)
  • NbPages: Number of Journal Pages
  • ScPages: Number of Journal Pages, Weighted by Simple Impact Factor
  • WScPages: Number of Journal Pages, Weighted by Recursive Impact Factor
  • ANbPages: Number of Journal Pages, Weighted by Number of Authors
  • AScPages: Number of Journal Pages, Weighted by Number of Authors and Simple Impact Factors
  • AWScPages: Number of Journal Pages, Weighted by Number of Authors and Recursive Impact Factors
  • AbsViews: Number of Abstract Views in RePEc Services over the past 12 months
  • Downloads: Number of Downloads through RePEc Serices over the past 12 months
  • AAbsViews: Number of Abstract Views in RePEc Services over the past 12 months, Weighted by Number of Authors
  • ADownloads: Number of Downloads through RePEc Serices over the past 12 months, Weighted by Number of Authors
  • Students: Record of graduates
  • Closeness: Closeness measure in co-authorship network
  • Betweenness: Betweenness measure in co-authorship network
  • NEP Cites: Breadth of citations across fields
  • Euclidian: Euclidian citation score
  • Wu index: Wu index

Averaging and aggregating methods

Let ri be the ranking for method i, si the score for that method, j all authors and N the number of selected ranking methods. Then, these rankings can be aggregated in the following ways:
  • harmonic mean: N 1/(Σi (1/ri)). This emphasizes good rankings.
  • arithmetic mean: (1/N) Σi ri. This penalizes poor rankings.
  • geometric mean: i ri)1/N. This does both of the above.
  • lexicographic: mini ri. This needs more explanations: the rankings according to each method are sorted in increasing order. Then, authors or institutions are classified first by their best rank, the second best rank, and so on. This emphasizes top rankings.
  • graphicolexic: maxi ri. A new word here. This is somewhat the opposite of the lexicographic ranking: the rankings according to each method are sorted in decreasing order. Then, authors or institutions are classified first by their worst rank (a minmax), the second worst being a tie breaker, etc. This emphasizes the worst rankings.
  • percent: (1/N) Σi (si/maxj sij). The best score in each method get 100%. The others get a percentage proportional to the best. Make then the average of those persentages. Emphasizes those that are well ranked by a large margin.
There are other ways to aggregate the methods, but they essentially are some combination of the above.

FAQ (Frequently asked questions)

Credits:

  • Citations from CitEc project by José Manuel Barrueco Cruz, University of Valencia, Spain. Hardware provided by Technical University of Valencia, Spain.
  • Abstract views and downloads from LogEc project by Sune Karlsson, Örebro University, Sweden.
  • Author registration by Ivan Kumanov, Minsk, Belarus.
  • Institutions database and ranking computations by Christian Zimmermann, University of Connecticut.
  • RePEc has been initiated by Thomas Krichel, Long Island University.
We do our best, but we cannot exclude errors.
IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.