Distributions for cited articles from individual subjects and years
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Summary
The results show that the power law is not a suitable model for collections of articles from a single subject and year, even for the purpose of estimating the slope of the tail of the citation data, and only the hooked power law and discrete lognormal distributions should be considered for subject-and-year-based citation analysis in future.
- Type
- article
- Published
- 2014-10-01
- Cited by
- 57
- References
- 26
- Access
- Open access
- OpenAlex
- https://openalex.org/W2083714175
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:2456120
Keywords
Log-normal distribution, Citation, Range (aeronautics), Set (abstract data type), Power law
References
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Cited by
- University citation distributions
- Why do papers have many Mendeley readers but few Scopus-indexed citations and vice versa?
- Mendeley readership altmetrics for medical articles: An analysis of 45 fields
- The influence of time and discipline on the magnitude of correlations between citation counts and quality scores
- Regression for citation data: An evaluation of different methods
- Status of Journals in the Field of Higher Education
- Geometric journal impact factors correcting for individual highly cited articles
- More precise methods for national research citation impact comparisons
- Towards a simple mathematical theory of citation distributions
- National, disciplinary and temporal variations in the extent to which articles with more authors have more impact: Evidence from a geometric field normalised citation indicator
- The precision of the arithmetic mean, geometric mean and percentiles for citation data: An experimental simulation modelling approach
- What Is a Complex Innovation System?
- The discretised lognormal and hooked power law distributions for complete citation data: Best options for modelling and regression
- Stopped sum models and proposed variants for citation data
- A comparison of two ways of evaluating research units working in different scientific fields
- A comparison of the Web of Science and publication-level classification systems of science
- Are the discretised lognormal and hooked power law distributions plausible for citation data?
- Are medical articles highlighting detailed statistics more cited
- Academic software downloads from Google Code: useful usage indicators?
- Are there too many uncited articles? Zero inflated variants of the discretised lognormal and hooked power law distributions
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