Research Impact

Article impact

Article level metrics or citation metrics are used to determine if a publication (commonly an article) has been cited by another work or works. The number of times an article is cited can indicate its importance to a particular field of study, the popularity of the topic, or contested nature. Citation count is useful, but it should not be the only criteria used to evaluate the impact of the article; the number of times a paper is cited does not indicate its actual quality. Certain disciplines tend to have low numbers of journals and usage, and thus should not be compared to other disciplines.

Article level metric overview

Article metric overview

Adapted from:

Colosimo, April. "Concept Map." Impact Measurements: Article-level metrics. McGill University. n.d. Web. 27 Aug. 2020. 

Article level metrics

Citation count is the most common metric used to assess the impact of journal articles. Citation counts are also used in the calculation of related article measures such as:

  • Article Influence Score
    • measures the average influence of a journal's articles over the first five years after publication
    • available in Web of Science, eigenfactor.org
  • Field Weighted Citation Impact (FWCI)
    • measures how an article's citation count compares to similar articles in the same field and time frame
    • available in Scopus
  • Relative Citation Ration (RCR)
    • a field- and time-adjusted metric is benchmarked to NIH publications to measure the scientific influence of a publication
    • available in Dimensions Plus and icite.org

The term "altmetrics" (or alternative metrics) is used to describe approaches to measure the impact of scholarship by using non-traditional citations, such as bookmarks, links, blog postings, inclusion in citation management tools, mentions and tweets,  to measure the importance of scholarly output. This is believed to help measure the impact of an article in a more comprehensive and objective way than just using citations. However, the use of altmetrics in formal processes is still very limited. Caution should be used to not rely on one particular measure in evaluating the importance of scholarship.