Do you know your h-index? Your personal impact factor? In recent years, a variety of indices have appeared that attempt to rank researchers’ impact on their fields, and databases have begun automatically calculating some of these indices for rapid retrieval. No one index is perfect, but they are increasingly used to rank individuals and institutions.

 

Following are a brief description of the various indices used to rate researchers, information on the databases that can be searched or formulae used to calculate indices for individual investigators and reported shortcomings of the indices.

  • Aggregate Citation Count – The total number of times an individual is cited is useful in comparing and ranking the impact of an investigator’s research within a specific discipline or institution. Author searches in the Scopus database rapidly retrieve the aggregate citation counts for a researcher and display them in on the Citation Tracker screen.
  • h-Index – The Hirsh Index attempts to reflect productivity (number of papers) and impact (number of citations) in one number. It is a researcher’s lowest number of papers with the same number of citations. For example, if 77 papers were each cited at least 77 times, the h-index is 77. However, if 2 of the 77 papers were only cited twice each, the h-index is 2. Scopus automatically calculates the h-index and displays it on the Citation Tracker screen for each author searched. The h-index discounts the disproportionate weight in the aggregate citation count of highly cited papers or papers that have not yet been cited.
    • A flaw of the h-index may be its inherent size dependence, in which larger numbers of publications generally command higher h-indexes. The h-index therefore rewards authors who publish many modestly well-cited articles, and punishes authors who publish profligately or rarely, new authors with few citation and authors who publish important papers judiciously. Like other measures, the h-index depends on the publication time period and subject discipline.
  • Personal Impact Factor – Like the h-index, the Personal IF also reflects productivity and impact in one number and varies by time period and discipline. It is the ratio of the number of citations in a given year to papers published by a researcher in the past two years, divided by the total number of articles published by the researcher in the past two years. One of its shortcomings is its short time frame.
  • Average Citations Per Paper – This measure is an attempt to weight impact in respect to output, since a greater number of publications tends to produce a greater number of citations. It is the sum of citations for a given time period divided by the number of publications. Different fields exhibit different average rates of citation, with which an individual’s average citations per paper score can be compared.
  • Percent Cited/Uncited Papers – This measure can reveal the amount of publications with no or very little influence. Author searches in Scopus display publications and the number of times each is cited or never cited on the Citation Tracker screen.
  • Individual Article Citation Count – The number of times an individual article has been cited is a roughly accurate gauge of its importance. Select a publication from an author search in Scopus, click on Citation Tracker, and examine the number of times the selected article was cited each year since publication to determine if citing articles peaked early or continue to rise, appear in important journals, are not self-citations, etc. Also referred to as Second-Generation Citation Count, this index depends on discipline and needs to be normalized by field.
  • Journal Impact Factor – This measure reflects the overall quality of a particular journal in a particular discipline, but says little if anything about the quality of a particular article in the journal. It is the ratio of the number of citations in a given year to papers published in a particular journal in the past two years.

Journal impact factors are easily identified in the Journal Citation Reports (JCR) database accessible in the Web of Knowledge online resource. JCR also supports new metrics, such as the Five-Year Impact Factor Trend Graph; the Eigenfactor, which uses citation data from all journals to rank the prestige and citation influence of a specific journal; and Rank-in-Category Tables, which evaluate jouranls in the context of multiple subject categories.