Citation And Bibliographic Coupling Between Authors In The Field Of

Leo Migdal

-Dec 5, 2025, 7:02 PM

citation and bibliographic coupling between authors in the field of

Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: CB. Performed the experiments: CB. Analyzed the data: CB CG. Wrote the paper: CB. Designed the software used in the analysis: CB.

Received 2014 Feb 7; Accepted 2014 May 15; Collection date 2014. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. This paper analyzes the effects of the co-authorship and bibliographic coupling networks on the citations received by scientific articles. It expands prior research that limited its focus on the position of co-authors and incorporates the effects of the use of knowledge sources within articles: references. By creating a network on the basis of shared references, we propose a way to understand whether an article bridges among extant strands of literature and infer the size of its research community and... Thus, we map onto the article – our unit of analysis – the metrics of authors' position in the co-authorship network and of the use of knowledge on which the scientific article is grounded.

Specifically, we adopt centrality measures – degree, betweenneess, and closeness centrality – in the co-authorship network and degree, betweenness centrality and clustering coefficient in the bibliographic coupling and show their influence on the citations... Findings show that authors' degree positively impacts citations. Also closeness centrality has a positive effect manifested only when the giant component is relevant. Author's betweenness centrality has instead a negative effect that persists until the giant component - largest component of the network in which all nodes can be linked by a path - is relevant. Moreover, articles that draw on fragmented strands of literature tend to be cited more, whereas the size of the scientific research community and the embeddedness of the article in a cohesive cluster of literature... Bibliographic coupling, like co-citation, is a similarity measure that uses citation analysis to establish a similarity relationship between documents.

Bibliographic coupling occurs when two works reference a common third work in their bibliographies. It is an indication that a probability exists that the two works treat a related subject matter.[1] Two documents are bibliographically coupled if they both cite one or more documents in common. The "coupling strength" of two given documents is higher the more citations to other documents they share. The figure to the right illustrates the concept of bibliographic coupling. In the figure, documents A and B both cite documents C, D and E.

Thus, documents A and B have a bibliographic coupling strength of 3 - the number of elements in the intersection of their two reference lists. Similarly, two authors are bibliographically coupled if the cumulative reference lists of their respective oeuvres each contain a reference to a common document, and their coupling strength also increases with the citations to other... If the cumulative reference list of an author's oeuvre is determined as the multiset union of the documents that the author has co-authored, then the author bibliographic coupling strength of two authors (or more... Bibliographic coupling can be useful in a wide variety of fields, since it helps researchers find related research done in the past. On the other hand, two documents are co-cited if they are both independently cited by one or more documents. The concept of bibliographic coupling was introduced by M.

M. Kessler of MIT in a paper published in 1963,[3] and has been embraced in the work of the information scientist Eugene Garfield.[4] It is one of the earliest citation analysis methods for document similarity... Furthermore, bibliographic coupling is a retrospective similarity measure,[5] meaning the information used to establish the similarity relationship between documents lies in the past and is static, i.e. bibliographic coupling strength cannot change over time, since outgoing citation counts are fixed. Author bibliographic coupling (ABC) is extended from the bibliographic coupling concept and holds the view that two authors with more common references are more related and have more similar research interests. This study aims to examine the association between author bibliographic coupling strength and citation exchange in eighteen subject areas.

The results show that there is no significant difference in the associations found across the subject areas. The correlation is positive and significant between the two factors in all subject areas, although it is stronger in some subject areas, such as Biomedical Engineering, than in others. For a closer investigation of the association between bibliographic coupling strength and citations exchanged between pairs of authors and also of ABC networks, a sample of highly cited authors in one of the subfields... The correlation is also highly significant among imetricians. This finding confirms Merton’s norm of universalism versus constructivists’ particularism. The investigation of thirty highly cited imetricians shows that Thelwall, M is in strong bibliographic coupling and citation relationships with the majority of the authors in the network.

He and Bar-Ilan have the strongest ABC and citation relationships in the network. Rousseau, R, Glanzel, W., Bornmann, L, Bar-Ilan, J, and Leydesdorff, L are also in strong ABC relationships with each other as well as other authors in the network. This is a preview of subscription content, log in via an institution to check access. Price excludes VAT (USA) Tax calculation will be finalised during checkout. http://incites.isiknowledge.com/common/help/h_field_category_oecd.html. Abrizah, A., Erfanmanesh, M., Rohani, V.

A., Thelwall, M., Levitt, J. M., & Didegah, F. (2014). Sixty-four years of informetrics research: Productivity, impact and collaboration. Scientometrics, 101(1), 569–585. We analyzed the structure of a community of authors working in the field of social network analysis (SNA) based on citation indicators: direct citation and bibliographic coupling metrics.

We observed patterns at the micro, meso, and macro levels of analysis. We used bibliometric network analysis, including the “temporal quantities” approach proposed to study temporal networks. Using a two-mode network linking publications with authors and a one-mode network of citations between the works, we constructed and analyzed the networks of citation and bibliographic coupling among authors. We used an iterated saturation data collection approach. At the macro-level, we observed the global structural features of citations between authors, showing that 80% of authors have not more than 15 citations from other works. At the meso-level, we extracted the groups of authors citing each other and similar to each other according to their citation patterns.

We have seen a division of authors in SNA into groups of social scientists and physicists, as well as into other groups of authors from different disciplines. We found some examples of brokerage between different groups that maintained the common identity of the field. At the micro-level, we extracted authors with extremely high values of received citations, who can be considered as the most prominent authors in the field. We examined the temporal properties of the most popular authors. The main challenge in this approach is the resolution of the author’s name (synonyms and homonyms). We faced the author disambiguation, or “multiple personalities” (Harzing, 2015) problem.

To remain consistent and comparable with our previously published articles, we used the same SNA data collected up to 2018. The analysis and conclusions on the activity, productivity, and visibility of the authors are relative only to the field of SNA. The proposed approach can be utilized for similar objectives and identifying key structures and characteristics in other disciplines. This may potentially inspire the application of network approaches in other research areas, creating more authors collaborating in the field of SNA. Competing Interests: The author has declared that no competing interests exist. Received 2022 Jun 16; Accepted 2023 Dec 22; Collection date 2024.

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Bibliometric studies offer numerous ways of analyzing scientific work. For example, co-citation and bibliographic coupling networks have been widely used since the 1960s to describe the segmentation of research and to look the development of the scientific frontier. In addition, co-authorship and collaboration networks have been employed for more than 30 years to explore the social dimension of scientific work. This paper introduces publication authorship as a complement to these established approaches. Three data sets of academic articles from accounting, astronomy, and gastroenterology are used to illustrate the benefits of publication authorship for bibliometric studies.

In comparison to bibliographic coupling, publication authorship produces significantly better intra-cluster cosine similarities across all data sets, which in the end yields a more fine-grained picture of the research field in question. Beyond this finding, publication authorship lends itself to other types of documents such as corporate reports or meeting minutes to study organizations, movements, or any other concerted activity. Bibliometric studies use publication data to describe the segmentation of research and to look at the development of the scientific frontier. The seminal works of the 1960s and 1970s [1–3] built networks of publications (vertices) connected by co-citation or bibliographic coupling (edges). Starting in the 1980s [4, 5], scholars turn to the social dimension of scientific research by looking at networks of authors (vertices) connected by author co-citation or co-authorship (edges).

Citation And Bibliographic Coupling Between Authors In The Field Of

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