Assessing books’ academic impacts via integrated computation of multi-level citation information
ISSN: 0264-0473
Article publication date: 8 June 2022
Issue publication date: 8 August 2022
Abstract
Purpose
Citations have been used as a common basis to measure the academic accomplishments of scientific books. However, traditional citation analysis ignored content mining and without consideration of citation equivalence, which may lead to the decline of evaluation reliability. Hence, this paper aims to integrate multi-level citation information to conduct multi-dimensional analysis.
Design/methodology/approach
In this paper, books’ academic impacts were measured by integrating multi-level citation resources, including books’ citation frequencies and citation-related contents. Specifically, firstly, books’ citation frequencies were counted as the frequency-level metric. Secondly, content-level metrics were detected from multi-dimensional citation contents based on finer-grained mining, including topic extraction on the metadata and citation classification on the citation contexts. Finally, differential metric weighting methods were compared with integrate the multi-level metrics and computing books’ academic impacts.
Findings
The experimental results indicate that the integration of multiple citation resources is necessary, as it can significantly improve the comprehensiveness of the evaluation results. Meanwhile, compared with the type differences of books, disciplinary differences need more attention when evaluating the academic impacts of books.
Originality/value
Academic impact assessment of books via integrating multi-level citation information can provide more detailed evaluation information and cover shortcomings of methods based on single citation data. Moreover, the method proposed in this paper is publication independent, which can be used to measure other publications besides books.
Keywords
Acknowledgements
This work is supported by the National Social Science Fund Project (No. 19CTQ031) and Open Fund Project of ISTIC – Clarivate Analytics Joint Laboratory for Scientometric (No. IT2142).
Citation
Zhou, Q. (2022), "Assessing books’ academic impacts via integrated computation of multi-level citation information", The Electronic Library, Vol. 40 No. 4, pp. 338-358. https://doi.org/10.1108/EL-03-2022-0060
Publisher
:Emerald Publishing Limited
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