G-index: Difference between revisions
Fgnievinski (talk | contribs) →top: (an author-level metric) |
if you need to say "in other words", that either means the first set of words wasn't good enough, or that you're being verbose. In this case, it looks like the latter. |
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The '''''g''-index''' is an index for quantifying [[scientific]] [[productivity]] based on [[scientific publication|publication]] record (an [[author-level metric]]). It was suggested in 2006 by Leo Egghe.<ref name="Egghe">Egghe, Leo (2006) Theory and practise of the g-index, Scientometrics, vol. 69, No 1, pp. 131–152. {{DOI|10.1007/s11192-006-0144-7}}</ref> |
The '''''g''-index''' is an index for quantifying [[scientific]] [[productivity]] based on [[scientific publication|publication]] record (an [[author-level metric]]). It was suggested in 2006 by Leo Egghe.<ref name="Egghe">Egghe, Leo (2006) Theory and practise of the g-index, Scientometrics, vol. 69, No 1, pp. 131–152. {{DOI|10.1007/s11192-006-0144-7}}</ref> |
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The index is calculated based on the distribution of [[citation]]s received by a given researcher's publications |
The index is calculated based on the distribution of [[citation]]s received by a given researcher's publications, such that given a set of articles [[ranking|rank]]ed in decreasing order of the number of citations that they received, the g-index is the unique largest number such that the top g articles received together at least g<sup>2</sup> citations. |
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:''Given a set of articles [[ranking|rank]]ed in decreasing order of the number of citations that they received, the g-index is the (unique) largest number such that the top g articles received (together) at least g<sup>2</sup> citations.'' |
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Just as with the [[h-index]], the g-index is a number which is the same for two different quantities: |
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This is in fact a rewriting of the definition |
This is in fact a rewriting of the definition |
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:<math>g \le \frac1g \sum_{{i\le g}}c_{i}</math> |
:<math>g \le \frac1g \sum_{{i\le g}}c_{i}</math> |
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[[File:Gindex1.jpg|thumb|275px|right| An example of a g-index (the raw citation data, plotted with stars, allows the h-index to also be extracted for comparison).]] |
[[File:Gindex1.jpg|thumb|275px|right| An example of a g-index (the raw citation data, plotted with stars, allows the h-index to also be extracted for comparison).]] |
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This means that in order to have a g-index of n an author that produces n articles should have, on average, n citations for each of them. Unlike the h-index, the g-index depends on the full citation count of very highly cited papers. Roughly, ''h'' is the number of papers of a quality threshold that rises as h rises; ''g'' allows citations from higher-cited papers to be used to bolster lower-cited papers in meeting this threshold. Therefore, in all cases g is at least h, and is in most cases higher.<ref name="Egghe"/> However, unlike the h-index, the g-index saturates whenever the average number of citations for all published papers exceeds the total number of published papers; the way it is defined, the g-index is not adapted to this situation. |
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The g-index has been characterized in terms of three natural axioms by Woeginger (2008).<ref>Woeginger, G.J. (2008) An axiomatic analysis of Egghe’s g-index, Journal of Informetrics, vol. 2, pp. 364–368. {{DOI|10.1016/j.joi.2008.05.002}}</ref> The simplest of these three axioms states that by moving citations from weaker articles to stronger articles, one's research index should not decrease. Like the [[h-index]], the g-index is a [[natural number]] and thus lacks in [[discriminatory power]]. Therefore, Tol (2008) proposed a [[rational number|rational]] generalisation.<ref>Tol, R.S.J. (2008) A rational, successive g-index applied to economics departments in Ireland, Journal of Informetrics, vol. 2, pp. 149–155. [http://ideas.repec.org/p/sgc/wpaper/147.html preprint]</ref> {{Clarify|reason=What rational generalization did he propose?|date=April 2010}} |
The g-index has been characterized in terms of three natural axioms by Woeginger (2008).<ref>Woeginger, G.J. (2008) An axiomatic analysis of Egghe’s g-index, Journal of Informetrics, vol. 2, pp. 364–368. {{DOI|10.1016/j.joi.2008.05.002}}</ref> The simplest of these three axioms states that by moving citations from weaker articles to stronger articles, one's research index should not decrease. Like the [[h-index]], the g-index is a [[natural number]] and thus lacks in [[discriminatory power]]. Therefore, Tol (2008) proposed a [[rational number|rational]] generalisation.<ref>Tol, R.S.J. (2008) A rational, successive g-index applied to economics departments in Ireland, Journal of Informetrics, vol. 2, pp. 149–155. [http://ideas.repec.org/p/sgc/wpaper/147.html preprint]</ref> {{Clarify|reason=What rational generalization did he propose?|date=April 2010}} |
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Revision as of 03:01, 18 September 2015
The g-index is an index for quantifying scientific productivity based on publication record (an author-level metric). It was suggested in 2006 by Leo Egghe.[1]
The index is calculated based on the distribution of citations received by a given researcher's publications, such that given a set of articles ranked in decreasing order of the number of citations that they received, the g-index is the unique largest number such that the top g articles received together at least g2 citations.
It can be equivalently defined as the number of highly cited articles, such that each of them has an average of g citations.
This is in fact a rewriting of the definition
as
This means that in order to have a g-index of n an author that produces n articles should have, on average, n citations for each of them. Unlike the h-index, the g-index depends on the full citation count of very highly cited papers. Roughly, h is the number of papers of a quality threshold that rises as h rises; g allows citations from higher-cited papers to be used to bolster lower-cited papers in meeting this threshold. Therefore, in all cases g is at least h, and is in most cases higher.[1] However, unlike the h-index, the g-index saturates whenever the average number of citations for all published papers exceeds the total number of published papers; the way it is defined, the g-index is not adapted to this situation.
The g-index has been characterized in terms of three natural axioms by Woeginger (2008).[2] The simplest of these three axioms states that by moving citations from weaker articles to stronger articles, one's research index should not decrease. Like the h-index, the g-index is a natural number and thus lacks in discriminatory power. Therefore, Tol (2008) proposed a rational generalisation.[3] [clarification needed]
Tol also proposed a collective g-index.
- Given a set of researchers ranked in decreasing order of their g-index, the g1-index is the (unique) largest number such that the top g1 researchers have on average at least a g-index of g1.
See also
References
- ^ a b Egghe, Leo (2006) Theory and practise of the g-index, Scientometrics, vol. 69, No 1, pp. 131–152. doi:10.1007/s11192-006-0144-7
- ^ Woeginger, G.J. (2008) An axiomatic analysis of Egghe’s g-index, Journal of Informetrics, vol. 2, pp. 364–368. doi:10.1016/j.joi.2008.05.002
- ^ Tol, R.S.J. (2008) A rational, successive g-index applied to economics departments in Ireland, Journal of Informetrics, vol. 2, pp. 149–155. preprint