Author impact metrics

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Google scholar's "cited by" feature for authors
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Contents

Last Update

  • Updated.jpg 14 June 2013

Introduction

See also Altmetrics | Bibliometrics | Citation analysis | Impact factors | Scholarly publishing and communication | Scopus vs. Web of Science | Webometrics

Author impact metrics refers to a whole range of quantitative methods of determining scholarly impact in the digital age. In the 21st century, scholars and researchers regularly locate papers that cite their work, book chapters and conference presentations. The resulting metrics are used to quantify and establish their impact in scholarly disciplines across science but also in the social sciences and humanities. Two related concepts are cited reference searching and journal impact metrics. To understand these concepts, it is important to emphasize how an author's impact is distinguished from other impact metrics. Although these metrics are related, it is important not to conflate the two or their related metrics.

Google scholar provides access to some idea of impact through its cited by feature but there are others tools that more accurately determine citation numbers. Google scholar, for example, does a fine job in locating all kinds of author references and articles from the footnotes and bibliographies of papers that are stored on the web. One of the best-known bibliometric tools is the Web of Science (WoS) which is a multidisciplinary database that more accurately aggregates citation data in the scholarly literature. WoS' main competitor for this purpose is Scopus.

In 2012, Higher Education Strategy looked at the publishing cultures in Canadian universities in their report entitled Making research count: analyzing Canadian academic publishing cultures which examines indices for scholarly impact such as the H-index.

  • a model for assessment of research impact

Newer indices measuring scholarly impact

1) Age-weighted citation rate (AWCR, AWCRpA) & AW-index

  • Inspired by Jin's The AR-index: complementing the h-index, the AWCR is an age-weighted citation rate where # of citations for a paper is divided by how old it is. Jin defines the AR-index as the square root of the sum of all age-weighted citation counts over all papers that contribute to the h-index. In Publish or Perish, papers are summed over as these represent the impact of the total body of work of a scholar. (This allows younger and less-cited papers to contribute to AWCR even though they may not yet contribute to the h-index.)

2) Contemporary h-index

  • Proposed in Generalized h-index for disclosing latent facts in citation networks, this index aims to improve on the h-index by giving more weight to recent articles, thus rewarding academics who maintain steady levels of activity. Age-related weighting is parametrized; the Publish or Perish implementation uses gamma=4 and-lta=1, like the authors did for their experiments. This means that for an article published during the current year, its citations account four times. For an article published 4 years ago, its citations account only one time. For an article published 6 years ago, its citations account 4/6 times, and so on.

3) Eigenfactor

Eigen.jpg
  • Eigenfactor.org is an academic research project at the University of Washington. Developed by West and Bergstrom, the Eigenfactor is a rating of the total importance of a scientific journal. Eigenfactor is reminiscent of Google's Pagerank algorithm in that journals are rated according to "link love" or the number of incoming citations. Moreover, citations from highly-ranked journals are weighted higher than poorly-ranked. An Eigenfactor score rises with the total impact of a journal. Therefore, journals that generate a higher impact in the field have a larger (or higher) Eigenfactor score.
  • Eigenfactor is also used in network analysis to develop methods to evaluate the influence of scholarly journals and map academic outputs in various disciplines.

4) Egghe's g-index

  • In the Theory and practice of the g-index, Egghe aims to improve on the h-index by giving more weight to highly-cited articles. The g-index is an index for quantifying scientific productivity based on publications and calculated based on the distribution of citations received by a given researcher's publications. So, given a set of articles ranked in decreasing order of the number of citations that they receive, the g-index is the (unique) largest number such that the top g articles received (together) at least g2 citations.

5) E-index

  • The e-index, complementing the h-index for excess citations is the square root of the surplus of citations in the h-core beyond h^2. One of the aims of the e-index is to differentiate between scientists with identical h-indices but different citations. Another advantage of the e-index is that it can reflect the contributions of highly cited papers of an author, as usually ignored by the h-index. Zhang says that the e-index "is a necessary h-index complement, especially for evaluating highly cited scientists or for precisely comparing the scientific output of a group of scientists having an identical h-index."

6) Google's I10-index

  • The I10-index indicates the # of papers an author has written that have been cited at least ten times by other scholars. It was introduced by Google in 2011 as part of their work on Google scholar, a search tool that locates academic and related papers. Due to some of the problems with inaccurate counts Google's I10 index has come under close scrutiny and criticism.

7) Hirsch's h-index

see also H-b index

  • In An index to quantify an individual's scientific research output, Hirsch aims to provide a single-number metric of an academic's impact, combining quality with quantity.
  • The H-factor is a measure of impact of individual scientists in their respective fields. When one scientist publishes n articles and is cited n times, an H-factor of n results. This rewards publication of many good articles but few poor ones. It is difficult to increase someone's H-factor by self-citation (a common problem). One or a few lucky "hits" will alone not improve your H-factor. H-factors become reliable once you have a substantial production of research output. It is important to emphasize that a single number cannot describe a scientist and the H-factor is only one measure of the impact of scholars.
  • Since Hirsch introduced the h index in 2005, this measure of academic impact has garnered widespread interest as well as proposals for other indices based on analyses of publication data such as the g index, h (2) index, m quotient, r index, to name a few. Several commonly used databases, such as Elsevier’s SciVerse Scopus, Thomson Reuters’ Web of Science, Google Scholar’s Citations and Microsoft’s Academic Search, provide h-index values for authors.

8) Individual h-index

9) R-Impact

10) Universal h-index

11) 'w-index' or Wu Index

  • In The w-index: a significant improvement of the h-index, Wu's index is described as similar to the h-index. According to Hirsch's criteria, a researcher with an h-index of 9 indicates that he or she has published at least 9 papers, each of which has been cited 9 or more times. The 'w-index' indicates that a researcher has published w papers, with at least 10w citations each. A researcher with a w-index of 24 means he or she has 24 papers with at least 240 citations each.
  • Wu says his index is an improvement on the h-index as it "accurately reflects the influence of a scientist’s top papers". He says it should be called the "10h-index". The w-index is easy to calculate using the Web of Knowledge, Scopus (Elsevier) or Google scholar and in the same way as the h-index by searching for a researcher's name and listing all of their papers in order with the highest cited papers cited first.

References
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