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Journal of Data and Information Science

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2543-683X
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Functions of Uni- and Multi-citations: Implications for Weighted Citation Analysis

Dangzhi Zhao
  • Corresponding author
  • School of Library and Information Studies, University of Alberta, Edmonton, Alberta T6G 2J4, Canada
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/ Alicia Cappello
  • School of Library and Information Studies, University of Alberta, Edmonton, Alberta T6G 2J4, Canada
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  • De Gruyter OnlineGoogle Scholar
/ Lucinda Johnston
  • School of Library and Information Studies, University of Alberta, Edmonton, Alberta T6G 2J4, Canada
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Published Online: 2017-02-18 | DOI: https://doi.org/10.1515/jdis-2017-0003

Abstract

Purpose: (1) To test basic assumptions underlying frequency-weighted citation analysis: (a) Uni-citations correspond to citations that are nonessential to the citing papers; (b) The influence of a cited paper on the citing paper increases with the frequency with which it is cited in the citing paper. (2) To explore the degree to which citation location may be used to help identify nonessential citations.

Design/methodology/approach: Each of the in-text citations in all research articles published in Issue 1 of the Journal of the Association for Information Science and Technology (JASIST) 2016 was manually classified into one of these five categories: Applied, Contrastive, Supportive, Reviewed, and Perfunctory. The distributions of citations at different in-text frequencies and in different locations in the text by these functions were analyzed.

Findings: Filtering out nonessential citations before assigning weight is important for frequency-weighted citation analysis. For this purpose, removing citations by location is more effective than re-citation analysis that simply removes uni-citations. Removing all citation occurrences in the Background and Literature Review sections and uni-citations in the Introduction section appears to provide a good balance between filtration and error rates.

Research limitations: This case study suffers from the limitation of scalability and generalizability. We took careful measures to reduce the impact of other limitations of the data collection approach used. Relying on the researcher’s judgment to attribute citation functions, this approach is unobtrusive but speculative, and can suffer from a low degree of confidence, thus creating reliability concerns.

Practical implications: Weighted citation analysis promises to improve citation analysis for research evaluation, knowledge network analysis, knowledge representation, and information retrieval. The present study showed the importance of filtering out nonessential citations before assigning weight in a weighted citation analysis, which may be a significant step forward to realizing these promises.

Originality/value: Weighted citation analysis has long been proposed as a theoretical solution to the problem of citation analysis that treats all citations equally, and has attracted increasing research interest in recent years. The present study showed, for the first time, the importance of filtering out nonessential citations in weighted citation analysis, pointing research in this area in a new direction.

Keywords: Weighted citation analysis; Citation function; Research evaluation; In-text citation analysis; Re-citation analysis

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About the article

Received: 2016-11-16

Accepted: 2016-11-20

Published Online: 2017-02-18

Published in Print: 2017-02-01


Citation Information: Journal of Data and Information Science, ISSN (Online) 2543-683X, DOI: https://doi.org/10.1515/jdis-2017-0003.

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© 2017 Dangzhi Zhao et al., published by De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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