🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge
Demo corpus. Scores are computed on a select set of biomedical paper/datasets and may be inaccurate for papers outside this corpus — DataRank relies on network effects that improve with scale. We aim to expand this into a fully open resource pending additional funding.

How fractional counting of citations affects the impact factor: Normalization in terms of differences in citation potentials among fields of science

Journal of the American Society for Information Science and Technology(2010)10.1002/asi.21450Source: DataRank Database

How fractional counting of citations affects the impact factor: Normalization in terms of differences in citation potentials among fields of science is a research paper published in Journal of the American Society for Information Science and Technology (2010). On theSindex it has a DataRank of 0.678. It has been cited 91 times.

N/A
0.678DataRank · unranked
0.678
91 citations · base score 4.5
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

The Impact Factors (IFs) of the Institute for Scientific Information suffer from a number of drawbacks, among them the statistics—Why should one use the mean and not the median?—and the incomparability among fields of science because of systematic differences in citation behavior among fields. Can these drawbacks be counteracted by fractionally counting citation weights instead of using whole numbers in the numerators? (a) Fractional citation counts are normalized in terms of the citing sources and thus would take into account differences in citation behavior among fields of science. (b) Differences in the resulting distributions can be tested statistically for their significance at different levels of aggregation. (c) Fractional counting can be generalized to any document set including journals or groups of journals, and thus the significance of differences among both small and large sets can be tested. A list of fractionally counted IFs for 2008 is available online at http:www.leydesdorff.net/weighted_if/weighted_if.xls The between-group variance among the 13 fields of science identified in the U.S. Science and Engineering Indicators is no longer statistically significant after this normalization. Although citation behavior differs largely between disciplines, the reflection of these differences in fractionally counted citation distributions can not be used as a reliable instrument for the classification.

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (0/2)
    Interoperable (0/2)
      Reusable (0/3)

        FAIR checklist signals are shown for context only and do not affect DataRank scoring.

        DataRank Breakdown

        Base Score 100%Citation Network 0%

        Base Score Contribution

        0.678

        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 →
        Why this DataRank?

        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.

        Base score B(p)
        log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
        Network N(p)
        Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
        Damping factor d = 0.85
        DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
        Self-citations excluded
        Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

        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.

        Read the full methodology →

        Authors (2)

        Related Papers (10)

        Journal of Informetrics(2011)
        co-cited
        10.1016/j.joi.2010.08.001
        Journal of the American Society for Information Science and Technology(2013)
        co-citedsame journal
        10.1002/asi.22911
        Journal of the American Society for Information Science and Technology(2010)
        co-citedsame journal
        10.1002/asi.21371
        Journal of the American Society for Information Science and Technology(2010)
        co-citedsame journal
        10.1002/asi.21354
        Journal of the American Society for Information Science and Technology(2011)
        co-citedsame journal
        10.1002/asi.21534