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Article-level metrics

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Article-level metrics provide insight into how individual research outputs are being accessed, shared, and cited. Unlike journal-level indicators, these metrics focus on the reach and engagement of a specific publication.

Common article-level indicators include:

1. Citation Count 

Citation counts record how many times a publication has been cited by other scholarly works, reflecting its visibility within academic research. They should not be interpreted as a measure of societal impact or overall value.

Citation counts are available through databases such as Scopus, Web of Science, OpenAlex, and Google Scholar, among others. However, each database only counts citations from publications indexed within its own system, so the same publication may show a different citation count depending on which database is consulted.

Advantages Limitations
  • widely used indicator of scholarly attention

  • show how often a publication has been used by other researchers

  • useful for comparing similar publication types within the same discipline and publication period
  • it is a quantitative indicator and should not be used to assess the quality or significance of a publication

  • it does not distinguish between positive, neutral, or negative citations

  • citations take time to accumulate, so recent publications may be disadvantaged

  • citation practices vary considerably between disciplines, making this metric inappropriate for cross-field comparisons 

2. Field-Weighted Citation Impact (FWCI) or Category Normalized Citation Impact (CNCI)

FWCI (Scopus) and CNCI (Web of Science) measure the number of citations received by a publication compared with the expected number of citations for similar publications of the same type, age, and discipline, based on the Scopus (FWCI) or Web of Science (CNCI) dataset. A value of 1.0 indicates performance at the global average; 1.50 indicates that the publication has been cited 50% more than expected. 

Advantages Limitations
  • compare publications on a like-for-like basis by accounting for discipline, publication type, and publication year

  • enable fair comparisons across different research year and field through normalisation
  • may not fully capture the impact of interdisciplinary research

  • scores can be influenced by a small number of highly cited papers, especially in fields with lower citation rates

  • scores are limited to publications indexed in the database used for the calculation

3. Highly Cited Publications (Top Percentile Metrics)

This indicator measures the proportion of publications that fall within the top 1%, 5%, 10%, or 25% most cited publications for their field and year of publication, based on data of a specific dataset (e.g. Scopus, Web of Science, OpenAlex or Dimensions).

A publication’s percentile is calculated by ranking all similar publications, those from the same year, subject area, and document type, based on how many citations they have received. The papers are ordered from the highest to the lowest number of citations, and the position of each paper is used to determine its percentile.

For example, if a paper has a percentile of 99, it means that 99% of comparable papers have received fewer citations, placing it among the top 1% most cited publications in its field for that year and document type.

Percentile thresholds are calculated annually, allowing outputs to be compared with other publications from the same year.

Advantages Limitations
  • identifies publications that rank among the most cited in their field and year

  • uses field normalisation, enabling comparisons across disciplines
  • more reliable for large publication sets than for individuals or small groups

  • comparisons can be misleading when entities differ substantially in size or publication output

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Questions?

For questions about publication data, assistance with your own bibliometric analysis, or advice on managing researcher profiles and improving the visibility of your research, email us at forskning@ub.uit.no.

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