Category Normalized Citation Impact (CNCI)

Calculating CNCI

The Category Normalized Citation Impact (CNCI) of a document is calculated by dividing the actual count of citing items by the expected citation rate for documents with the same document type, year of publication and subject area. When a document is assigned to more than one subject area an average of the ratios of the actual to expected citations is used. The CNCI of a set of documents, for example the collected works of an individual, institution or country/region, is the average of the CNCI values for all the documents in the set.

For a single paper that is only assigned to one subject area, this can be represented as:

single-paper-cnci.gif

For a single paper assigned to multiple subjects, the CNCI can be represented as the average of the ratios for of actual to expected citations for each subject area:

single-paper-multiple-subjects-cnci.gif

 

For a group of papers, the CNCI value is the average of the values for each of the papers:

group-papers-cnci.gif

Equation Key
e Expected citation rate or baseline
c Times cited
p Number of papers
f The field or subject area
t Year
d Document Type
n The number of subjects to which a paper is assigned
i Entity being evaluated (institution, country/region, person, etc.)

 

Explorers other than Research Area with the Research Area filter applied

  • When a document is in that unique category, a single CNCI is calculated
  • When a document is in that category plus other (multiple categories), then a CNCI is calculated for each category and the average result is provided as CNCI

Research Area explorer with one category filter

  • When a document is in that unique category, a single CNCI is calculated
  • When a document is in that category plus other (multiple categories), then a single CNCI is calculated and provided, based on the category in the filter.

This is why there can be some small differences in the values when comparing these contexts.

CNCI is a valuable and unbiased indicator of impact irrespective of age, subject focus, or document type. Therefore, it allows comparisons between entities of different sizes and different subject mixes.

  • A CNCI value of 1 represents performance at par with world average.
  • Values above 1 are considered above average.
  • Values below 1 are considered below average.
  • A CNCI value of 2 is considered twice world average.

A quirk of the way we calculate baselines (whole counting of subjects for papers in more than one subject category) and CNCI (fractional counting of subjects for papers in more than one subject category) result in the CNCI of the world not being equal to one exactly.

CNCI is an ideal indicator for benchmarking at all organizational levels (author, institution, region etc). You can also use CNCI to identify impactful sub-sets of documents and assess any research activity. For example, an institution may use the CNCI to assess which collaborations are most impactful or identify new potential collaboration opportunities. An institution may also use CNCI to identify the performance of up-and-coming researchers compared to established ones, and aid with faculty recruitment by assessing candidates. As a funding organization, you may use the CNCI as a quantitative performance indicator to monitor the performance of funded projects, or assess the track record of a research teams applying for new funding.

Known Issues Using CNCI

When dealing with small sets of publications, for example, the publications of one individual, the CNCI values may be inflated by a single highly cited paper.

Because CNCI is an average, when looking at larger sets of publications, such as the collected works of an institution, very highly cited papers can have a large influence on the CNCI value.

The baseline values for current year can be very low and therefore the CNCI values for current year can fluctuate more than expected.

Steps to Resolve CNCI Issues

  • Use the CNCI value alongside other indicators to have a picture of performance as a whole and to identify anomalies and data artifacts.
  • Use larger sets of publications when possible, for example, by extending the time period or expanding the number of subjects covered.
  • Show care when analyzing documents from most recent publication years. Include documents from a range of years for more meaningful analysis.
  • Limit your analysis to significant research publications to the document type of Article or Review. If appropriate, to aid increased coverage of some fields, consider document types Book Chapters and Conference Proceedings.
  • Always use citation indicators to aid and not replace human judgment.

Complementary Indicators Useful with CNCI

  • Journal Normalized Citation Impact
  • % Documents in Top 1% and % Documents in Top 10%
  • Average Percentile
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