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Semantic similarity-based credit attribution on citation paths: a method for allocating residual citation to and investigating depth of influence of scientific communications

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Abstract

This study proposes a method for assessing the impact of scientific communication on their citation paths beyond conventional direct citations. The proposed method considers the contribution of scientific communication to their nth generation citations as a basis for calculating residual citations. Residual citations that are lost due to citation practices termed “Obliteration by Incorporation” and the “Palimpsestic Syndrome” in consequent citations in the second, third or nth generations are reconstituted. The proposed method is based on the semantic similarity between the citation contexts of a publication and those of its nth generation citations in their n + 1th generation citations. The proposed method was demonstrated using a sample of biomedical publications with ten base articles and their five generations of citations. Like the cascading citation system, residual citations accruing to articles from their generations of citations decreased as the number of generations increased. However, residual citation weights accrued to publications at all generation levels were statistically different between the proposed residual citation and the cascading citation system. This method introduces a new frontier that assesses the depth of impact of a publication (beyond the conventional direct citation level).

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Data availability

The datasets generated and/or analyzed during the current study are available in the Mendeley repository, through https://doi.org/10.17632/6fgjxkv28d.3.

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Acknowledgements

This study is a modified version of a pre-print (Asubiaro & Ajiferuke, 2021) that was deposited in Research Square. This journal publication is part of the first author’s doctoral thesis and contains texts that have been copied verbatim from the thesis. The contributions of the first author's doctoral thesis committee members- Professor Robert Mercer, Computer Science Department, University of Western Ontario, London, Canada and Professor Victoria Rubin, Library and Information Science Program, University of Western Ontario, London, Canada are acknowledged.

Funding

The first author received the Western Graduate Research Scholarships from September 2016 and September 2020 and Ontario Graduate Scholarships and the Queen Elizabeth II Graduate Scholarships in Science and Technology (OGS/QEII-GSST), 2019 summer term to 2020 winter term.

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Authors and Affiliations

  1. Equity, Diversity and Inclusivity Research Analyst, Performance Analytics, and Institutional Research, University of Alberta, Edmonton, Canada

    Toluwase Victor Asubiaro

  2. Faculty of Media and Information Studies, University of Western Ontario, London, Canada

    Isola Ajiferuke

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  1. Toluwase Victor Asubiaro
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Correspondence to Toluwase Victor Asubiaro.

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Asubiaro, T.V., Ajiferuke, I. Semantic similarity-based credit attribution on citation paths: a method for allocating residual citation to and investigating depth of influence of scientific communications. Scientometrics 127, 6257–6277 (2022). https://doi.org/10.1007/s11192-022-04522-3

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