H-index - Alternatives and Modifications

Alternatives and Modifications

Various proposals to modify the h-index in order to emphasize different features have been made:. As the variants have proliferated, comparative studies have become possible and they demonstrate that most proposals do not differ significantly from the original h-index as they remain highly correlated with it.

  • An individual h-index normalized by the average number of co-authors in the h-core has been introduced by Batista et al. They also found that the distribution of the h-index, although it depends on the field, can be normalized by a simple rescaling factor. For example, assuming as standard the hs for biology, the distribution of h for mathematics collapse with it if this h is multiplied by three, that is, a mathematician with h = 3 is equivalent to a biologist with h = 9. This method has not been readily adopted, perhaps because of its complexity. It might be simpler to divide citation counts by the number of authors before ordering the papers and obtaining the h-index, as originally suggested by Hirsch.
  • The m-index is defined as h/n, where n is the number of years since the first published paper of the scientist; also called m-quotient.
  • A generalization of the h-index and some other indices that gives additional information about the shape of the author's citation function (heavy-tailed, flat/peaked, etc.) was proposed by Gągolewski and Grzegorzewski.
  • Successive Hirsch-type-index introduced independently by Kosmulski and Prathap. A scientific institution has a successive Hirsch-type-index of i when at least i researchers from that institution have an h-index of at least i.
  • Bornmann, Mutz, and Daniel recently proposed three additional metrics, h2 lower, h2 center, and h2 upper, to give a more accurate representation of the distribution shape. The three h2 metrics measure the relative area within a scientist's citation distribution in the low impact area, h2 lower, the area captured by the h-index, h2 center, and the area from publications with the highest visibility, h2 upper. Scientists with high h2 upper percentages are perfectionists, whereas scientists with high h2 lower percentages are mass producers. As these metrics are percentages, they are intended to give a qualitative description to supplement the quantitative h-index.
  • The g-index proposed by Egghe can be seen as the h-index for an averaged citations count.
  • K. Dixit and colleagues argue that "For an individual researcher, a measure such as Erdős number captures the structural properties of network whereas the h-index captures the citation impact of the publications. One can be easily convinced that ranking in coauthorship networks should take into account both measures to generate a realistic and acceptable ranking." Several author ranking systems such as eigenfactor (based on eigenvector centrality) have been proposed already, for instance the Phys Author Rank Algorithm.
  • The c-index accounts not only for the citations but for the quality of the citations in terms of the collaboration distance between citing and cited authors. A scientist has c-index n if n of N citations are from authors which are at collaboration distance at least n, and the other (Nn) citations are from authors which are at collaboration distance at most n.
  • An s-index, accounting for the non-entropic distribution of citations, has been proposed and it has been shown to be in a very good correlation with h
  • The e-index, square root of surplus citations for the h-set beyond h2, complements the h-index for ignored citations, and therefore is especially useful for highly cited scientists and for comparing those with the same h-index (isohindex group).
  • Because the h-index was never meant to measure future publication success, recently, a group of researchers has investigated the features that are most predictive of future h-index (Nature article). It is possible to try the predictions using an online tool

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