Bibliometrics can help you to make decisions about where to publish your research and how to get information about the impact of published research. Bibliometrics is measuring impact not quality.
This guide provides information about the most common tools that individual researchers or research administrators can use to measure the impact of their own or their institutions impact.
It also tries to help researchers to raise the visibility of publications and subsequently make it better known.
Article/Book Impact: The impact of particular works, such as journal articles, conference proceedings, and books, can be measured by the number of times they are cited by other works.
Journal impact: The impact of particular academic journals can be measured by the number of times their articles are cited and where they are cited.
Researcher impact: The number of works a researcher has published and the number of times these works have been cited can be an indicator for the impact of an individual researcher
Institutional impact: The prestige of a department or area of research within an institution can be measured by the collective impact of its individual researchers compared to those at other institutions
Scopus CiteScore™, a free Elsevier product, measures citation impact for journals, book series, conference proceedings and trade journals. The CiteScore Tracker is calculated monthly.
h5-index is the h-index for articles published in the last 5 complete years. It is the largest number h such that h articles published in 2007-2011 have at least h citations each.
The h-index, or Hirsch index, measures the impact of a particular scientist rather than a journal. "It is defined as the highest number of publications of a scientist that received h or more citations each while the other publications have not more than h citations each (Schreiber, 2008a)." The h-index is included in Web of Science. For example, a scholar with an h-index of 5 had published 5 papers, each of which has been cited by others at least 5 times.
Expresses the journal's number of articles (h) that have received at least h citations. It quantifies both journal scientific productivity and scientific impact and it is also applicable to scientists, countries, etc.
The G-index was proposed by Leo Egghe in his paper "Theory and Practice of the G-Index" in 2006 as an improvement on the H-Index.
G-Index is calculated this way: "[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 g^2 citations." (from Harzig's Publish or Perish Manual)
Created by Google Scholar and used in Google's My Citations feature. i10-Index = the number of publications with at least 10 citations. This very simple measure is only used by Google Scholar, and is another way to help gauge the productivity of a scholar.
The m-quotient aims at weighing the period of academic Endeavour so that even junior scientists attain the importance that they deserve. Thus, if n=number of years since the first published paper of the scientist, the m-quotient=h-index/n. However, the m-quotient may not stabilize until later in the scientist's career. for researchers in the early part of their career, who have low h indices, small changes in the h-index can lead to large changes in the m-quotient. Hirsch suggests the researcher's first published paper may not always be the appropriate starting point, especially if it was a minor contribution that was published well before the academic's period of sustained productivity. Although the m-quotient adds time as a weighting factor, it does not cater to the major disadvantages of the h-index including quality of publication and quality of citation.
You can join ImpactStory Profiles for free by using a Twitter account.
From ImpactStory.com: "Impactstory is an open-source, web-based tool that helps scientists explore and share the diverse impacts of all their research products—from traditional ones like journal articles, to emerging products like blog posts, datasets, and software. By helping scientists tell data-driven stories about their impacts, we're helping to build a new scholarly reward system that values and encourages web-native scholarship."