How to analyze percentile citation impact data meaningfully in bibliometrics: The statistical analysis of distributions, percentile rank classes, and top‐cited papers is a research paper published in Journal of the American Society for Information Science and Technology (2013). On theSindex it has a DataRank of 0.617. It has been cited 60 times.
According to current research in bibliometrics, percentiles (or percentile rank classes) are the most suitable method for normalizing the citation counts of individual publications in terms of the subject area, the document type, and the publication year. Up to now, bibliometric research has concerned itself primarily with the calculation of percentiles. This study suggests how percentiles (and percentile rank classes) can be analyzed meaningfully for an evaluation study. Publication sets from four universities are compared with each other to provide sample data. These suggestions take into account on the one hand the distribution of percentiles over the publications in the sets (universities here) and on the other hand concentrate on the range of publications with the highest citation impact—that is, the range that is usually of most interest in the evaluation of scientific performance.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.617
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.