Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal
2010

Statistical Validation of Citation Distribution Models

Sample size: 2184 publication 10 minutes Evidence: high

Author Information

Author(s): Michael J Stringer, Marta Sales-Pardo, Luís A Nunes Amaral

Primary Institution: Northwestern University

Hypothesis

Is the citation distribution of scientific papers consistent with a discrete lognormal distribution?

Conclusion

The study concludes that the discrete lognormal distribution is a globally accurate model for the eventual impact of scientific papers published in single-discipline journals.

Supporting Evidence

  • 30 out of 2184 journals showed citation distributions inconsistent with a discrete lognormal distribution.
  • Large, multidisciplinary journals were over-represented among those inconsistent journals.
  • The study suggests that citation distributions are lognormal within a discipline.

Takeaway

This study looks at how often scientific papers get cited and finds that most papers follow a predictable pattern, like a lognormal distribution.

Methodology

The study performed a large-scale empirical analysis of citation data from the Web of Science database, focusing on journals with a steady-state citation distribution.

Potential Biases

Potential biases may arise from the exclusion of certain journals and the reliance on citation data that can change over time.

Limitations

The study may not account for all types of journals, particularly those with fewer than 50 articles per year or those that are not primary research literature.

Participant Demographics

The analysis included journals from various scientific fields represented in the Web of Science database.

Statistical Information

P-Value

p<0.001

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1002/asi.21335

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