Bibliometrics is a group of mathematical and statistical methods that are used to analyse and measure the quantity and quality of different forms of publications. Basically there are three types of bibliometric indicators:

• Quantity indicators: These measure the productivity of a researcher.
• Quality indicators: These measure the performance of a researcher.
• Structural indicators: These measure the connection between publications, authors, and areas of research.

Bibliometric indicators influence funding decisions, appointments, and promotions of researchers; therefore, it is important for scholars as well as organisations.

Journal-level Bibliometric

Impact Factor

Journal Impact Factor is the most prevalent bibliometric indicator among journals. It is an assessment of how frequently articles published in a particular journal are cited on an average in the two years following their publication. The greater the impact factor, the more prominent the journal. The other well-known and widely accepted bibliometric indicators are:

SCImago Journal Ranking (SJR)

SJR takes into account both the number of citations received and the significance of the journals from where such citations are sourced. SJR computation uses an algorithm similar to Google PageRank.

Source Normalized Impact per Paper (SNIP)

SNIP assesses the impact of contextual citation by measuring citations based on the total number of citations in a particular field of study. SNIP is defined as the ratio of a journal’s citation count per paper and the citation potential in its subject field.

Impact per Publication (IPP)

This mode of measurement calculates the ratio of citations in a year (Y) to scholarly papers published in the three previous years (Y-1, Y-2, Y-3) divided by the number of scholarly papers published in those same years (Y-1, Y-2, Y-3).

Author-level Bibliometric

Bibliometric indicators measuring the impact of individual authors are known as author-level metrics.

H-index

H-index measures both the productivity and impact of the published work of a researcher. It is the most well-known author-level metric at present.
However, h-index has the following shortcomings:
• It does not account for highly cited papers, i.e. the h-index of the author remains the same whether their most highly cited paper has 100 or 10 citations.
• It does not take into consideration the career span of the author. This is because it is only dependent on productivity and impact. Therefore, authors with longer career spans and more publications will always have higher scores.

To overcome these shortcomings of h-index, the following variants were proposed:

G-index

It is an author-level metric for quantifying scientific productivity based on publication record. G-index is found by analysing the distribution of citations received by a specific researcher’s publications.

M-index

It is defined as the h-index divided by the number of years the researcher has been publishing papers.