The h-index was proposed by Hirsch (2005). It is defined as follows: «A scientist has h-index if h of his/her Np papers have at least h citations each, and the other (Np-h) papers have no more than h citations each»
The advantage of the h-index is that it combines an assessment of both quantity (number of papers) and quality (impact or citations to these paper) (Glänzel, 2006). Am academic cannot have a high h-index without publishing a substantial number of paper. However, these papers need to be cited by others academics in order to count for the h-index.(Anne-Will Harzing, 2011)
A disadvantage of the h-index is that it ignores the number of citations to each individual article over and above what is needed to achieve a certain h-index. Once a paper belongs to the top h papers, its subsequent citations no longer count. Hence, in order to give more weight to highly-cited articles Leo Egghe (2006) proposed the g-index.
Hi Ibrain - this is an often-asked question on RG.
H-index, as you correctly point out, has pros and cons. The attached chapter, related to publishing research findings, supports your suggestions. At the end of the day - it's how the publishers and authors use and navigate the system.
Good to read the original paper which started the h factor story:
https://arxiv.org/pdf/physics/0508025v5.pdf
It shows why h factor is a rather relevant -though emprical- information and formula (15) is proposed to take into account number of co-authors.
They are other renormalization factors like m=h/years of publications, and so on.
Thank partners for your answers...certainly, the h-index improves bibliometry and in this way it allows quantify the individual output of scientists from different points of view.
El índice H revolucionó la menra en que se cuantifica y mide la producción científica. Es una forma muy práctica, con sus ventajas y desventajas, de medir las contribuciones a la ciencia...
El índice H es un indicador bibliométrico que toma potencia como referente de la trayectoria investigadora en comparación con el factor de impacto, principalmente porque unifica la difusión e impacto. Muchos investigadores afirman que: “su principal debilidad es que no aprecia las colas de citas por encima ni por debajo del índice y promociona a los productores masivos de artículos y penaliza a los selectivos”. (Túñez M y Pablos JM; 2013)
The h-index is computed based on the highly cited papers of an author and the number of citations these papers have received from other articles. As the h-index attempts to measure a researcher's impact over time, the longer a researcher has been publishing, the higher the h-index would be! As an alternate metric to h-index, i10-Index has been created by Google Scholar. It is a whole number indicating the number of publications of a particular scientist with at least 10 citations. However, it is used only by Google Scholar.
I agree with Roman Anufriev, about the disadvantages of h-index. Its not any differences about the first author and other co-authors.
Furthermore, authors working in the small departments, have lower possibilities to publish more papers, and to be evolved as co-authors.
The h-index is not something that needs to be calculated on a daily basis, but it's good to know where you are for several reasons. First, climbing the h-index ladder is something worth celebrating. If it's worth opening a bottle of champagne or just getting a cafe latte that's up to you, but seriously take your time to celebrate this achievement (there aren't that many in academia). But more importantly, the h-index is one of the measures funding agencies or the university's hiring committee calculate when you apply for a grant or a position. Given the often huge number of applications, the h-index is calculated in order to rank candidates and apply a pre-filter. Of course, funding agencies and hiring committees do use tools for calculating the h-index, and so can you.
And I agree with u.The advantage is it ignores the no. of citations to each individual article over & above what is needed to attain certain h-index
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