Hybrid Model for Conducting Multiple Citation Analysis Operations Using the Same Citation Data
Authors
-
Department of Computer Science, Assam University, Silchar – 788011, Assam
Bhagwan Sahay Meena -
Munshi Premchand Mahavidyalaya, Siliguri – 734001, West BengalSharmila Bose Majumder
-
Department of Computer Science, Central University of South Bihar, Gaya – 824236, BiharNemi Chandra Rathore
-
Jaypee Institute of Information Technology, Noida – 201309, Uttar PradeshNeeraj Jain
DOI:
https://doi.org/10.17821/srels/2024/v61i3/171397Keywords:
Bibliographic Coupling, Citation Density Analysis, Citation Network, Co-Citation AnalysisAbstract
This study proposes a hybrid model, which can be used for conducting various citation analysis operations over a set of research works/papers interconnected with each other through their citations and references. Citation analysis of papers becomes important while evaluating their role and influence in a particular field and understanding their relation and connectivity of content with other important documents in the same field. The citation analysis methods can further be used for tracing the relationship between domains, keywords, and many other relative factors, based on the criteria considered for citation analysis operation. The research in the field of citation analysis, traditionally focussed on developing new citation analysis methods for better evaluation or ranking of the papers. This paper proposes a model, where multiple existing citation analysis operations can be implemented in a single platform. The proposed model calculates the result for co-citation analysis, bibliographic coupling, and citation density analysis. The process involved in the development of this model is discussed in detail in the later part of the manuscript. The process is based on computational coding, and hence special attention needs to be paid to the proper arrangement of papers in tabular form, based on the information of their year of publication and their citation network data. An algorithm for the model has been proposed in the later part of the manuscript that is based on the code formulated to find the relative data for conducting the operations.
Downloads
Metrics
References
Pendlebury, A. D. (2001). Handbook bibliometrics: Eugene Garfield and the Institute for Scientific Information. Berlin, De Gruyter Saur.
Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4):265-269. https://doi.org/10.1002/asi.4630240406
Boyack, K. W., & Richard, K. (2010). Co-citation analysis, bibliographic coupling, and direct citation: Which citation model represents the research front most accurately? Journal of the American Society for Information Science and Technology. 61(12), 2389-2404. https://doi.org/10.1002/ asi.21419
Surwase, G., Sagar, A., Kademani, B. S. & Bhanumurthy, K. (2011). Co-citation analysis: An overview [Conference presentation]. Beyond Librarianship: Creativity, Innovation and Discovery, Mumbai, India.
Jeong, Y. K., Song, M., & Ding, Y. (2014). Content-based author co-citation analysis. Journal of Informetrics, 8(1), 197-211. https://doi.org/10.1016/j.joi.2013.12.001
McLaren, C. D., & Bruner, M. W. Citation network analysis. International Review of Sport and Exercise Psychology, 15(1), 179-198. https://doi.org./10.1080/1750984X.2021.1989705
Allahabadi, S., Eftekhari, A., Feeley E. S., Feeley, T. B., Lansdown, A. D. (2010). Influential and highest cited shoulder instability articles: A bibliometric analysis. Investigation performed at the Department of Orthopedic Surgery, University of California, San Francisco.
Zavaraqi, R. (2010). Author Co-Citation Analysis (ACA): A powerful tool for representing implicit knowledge of scholar knowledge workers [Conference presentation]. Sixth International Conference on Webometrics, Informetrics and Scientometrics and Eleventh COLLNET Meeting, University of Mysore, India.
Moed, H. F. (2005). Citation analysis in research evaluation. Dordrecht: Springer.
Newman, M. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Science, United States of America, 101(1), 5200-5. https://doi.org/10.1073/pnas.0307545100 PMid:14745042 PMCid:PMC387296
DeSilva, L.G., Lawson, K., Hughes, T., Jones, R. (2016). Citation analysis of the 100 most common articles regarding distal radius fractures. Journal of Clinical Orthopedics and Trauma, 8(1), 73-75. https://doi.org/10.1016/j. jcot.2016.09.005 PMid:28360502 PMCid:PMC5359520
Freeman, G. H., Ding, Y., & Milojevic, S. (2013). Citation Content Analysis (CCA): A framework for syntactic and semantic analysis of citation content. Journal of the American Society for Information Science and Technology, 64(7), 1490-1503. https://doi.org/10.1002/asi.22850
Gipp, B. Citation proximity analysis [Paper presentation]. Seminar on Information Access at the School of Information, University of California, Berkeley.
Persson, O. (2010). Identifying research themes with weighted direct citation links. Journal of Informatics, 4(3), 415-422. https://doi.org/10.1016/j.joi.2010.03.006
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Journal of Information and Knowledge
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All the articles published in Journal of Information and Knowledge are held by the Publisher. Sarada Ranganathan Endowment for Library Science (SRELS), as a publisher requires its authors to transfer the copyright prior to publication. This will permit SRELS to reproduce, publish, distribute and archive the article in print and electronic form and also to defend against any improper use of the article.
