Bibliometrics

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Bibliometrics is a set of methods used to study or measure texts and information. Citation analysis and content analysis are commonly used bibliometric methods. While bibliometric methods are most often used in the field of library and information science, bibliometrics have wide applications in other areas. In fact, many research fields use bibliometric methods to explore the impact of their field, the impact of a set of researchers, or the impact of a particular paper. Historically bibliometric methods have been used to trace relationships amongst academic journal citations. Citation analysis, which involves examining an item's referring documents, is used in searching for materials and analyzing their merit. Citation indices, such as Institute for Scientific Information's Web of Science, allow users to search forward in time from a known article to more recent publications which cite the known item. Data from citation indexes can be analyzed to determine the popularity and impact of specific articles, authors, and publications. Using citation analysis to gauge the importance of one's work, for example, is a significant part of the tenure review process. Information scientists also use citation analysis to quantitatively assess the core journal titles and watershed publications in particular disciplines; interrelationships between authors from different institutions and schools of thought; and related data about the sociology of academia. Some more pragmatic applications of this information includes the planning of retrospective bibliographies, "giving some indication both of the age of material used in a discipline, and of the extent to which more recent publications supersede the older ones;" indicating through high frequency of citation which documents should be archived; comparing the coverage of secondary services which can help publishers gauge their achievements and competition, and can aid librarians in evaluating "the effectiveness of their stock"^[1] There are also some limitations to the value of citation data. They are often incomplete or biased; data has been largely collected by hand (which is expensive), though citation indexes can also be used; incorrect citing of sources occurs continually; thus, further investigation is required to truly understand the rationale behind citing to allow it to be confidently applied^[2] Although citation analysis is nothing new (the Science Citation Index began publication in 1961), greater computing power is making it more useful and widespread. Google's PageRank is based on the principle of citation analysis. Patent citation maps are also based upon citation analysis (in this case, the citation of one patent by another). Other bibliometrics applications include: creating thesauri; measuring term frequencies; exploring grammatical and syntactical structures of texts; measuring usage by readers. In 2003 Charles Murray published the results of a vast bibliometric study supposed to reveal the 'significant figures' in the arts and sciences. Some 4002 people are ranked in his lists compiled for 12 domains (8 scientific disciplines, literature, philosophy, arts).

The H-index

The h-index, also known as the Hirsch number is a number suggested by Jorge E. Hirsch in 2005 for the quantification of scientific output of individual scientific authors. It is based on the citations each article (paper) of an author gets. Hirsch writes:

A scientist has index h if h of his/her N_p papers have at least h citations each, and the other (N_p - h) papers have fewer than h citations each.

In other words, a scholar with an index of h has published h papers with at least h citations each. The H-index is the result of the maximum of the balance between the number of publications and the number of citations per publication. This number has several advantages over other criteria, e.g., compared against the total number of citations, it is not very sensitive to a single paper that has many citations. And the H-index is designed to improve upon simpler measures such as the total number of citations or publications, to distinguish truly influential scientists from those who simply publish many papers. H-index has been suggested for use in academic promotions, tenure, grant funding, and prediction of winning of the Nobel Prize. Online web programs are available to directly calculate a scientist's H-index number using Google Scholar. Google Scholar and Web of Science can also be used to manually determine the H-index, but will produce different numbers from classic citation index-based counts, as its citation numbers are sometimes different. H-index values are also only comparable for scientists working in the same field; citation patterns differ widely among different fields. For research fields such as Computer Science, Google Scholar is liable to produce a high h, largely due to traditional citation indices' poor coverage of high impact conferences and Google Scholar's good coverage of web-based publications. For other fields that publish more in journals and whose scholars are less inclined to put pre-prints on the Web, a Google Scholar-based H is likely to be lower. More details of criticisms may be founded at H-index

References and external links

H-index calculator of scientist impact using Google Scholar.
Murray, Charles (2003), Human Accomplishment: the pursuit of excellence in the arts and sciences 800 to 1950 [ISBN 0-641-65181-3]
Hirsch, Jorge E., (2005), An index to quantify an individual's scientific research output. Available from arXiv: [1].
Noruzi, Alireza (2005). "Google Scholar: The New Generation of Citation Indexes," Libri, 55(4), 170-180.
Science-Metrix

^ Nicholas, David and Maureen Ritchie. Literature and Bibliometrics London: Clive Bingley: 1978. (12-28).
^ Nicholas, David and Maureen Ritchie. Literature and Bibliometrics London: Clive Bingley: 1978. (28-29).