Browse > Article
http://dx.doi.org/10.4275/KSLIS.2022.56.4.269

Comparison Analysis of Co-authorship Network and Citation Based Network for Author Research Similarity Exploration  

Jeeyoung, Yoon (Department of Library and Information Science, Yonsei University)
Min, Song (Department of Library and Information Science, Yonsei University)
Publication Information
Journal of the Korean Society for Library and Information Science / v.56, no.4, 2022 , pp. 269-284 More about this Journal
Abstract
Exploring research similarity of researchers offers insight on research communities and potential interactions among scholars. While co-authorship is a popular measure for studying research similarity of researchers, it cannot provide insight on authors who have not collaborated yet. In this work, we present novel approach to capture research similarity of authors using citation information. Extensive study is conducted on DATA & KNOWLEDGE ENGINEERING (DKE) publications to demonstrate and compare suggested approach with co-authorship based approach. Analysis result shows that proposed approach distinguishes author relationships that is not shown in co-authorship network.
Keywords
Author research similarity analysis; Co-authorship network; Citation based author analysis; Network Analysis; Data & Knowledge Engineering;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 Zhao, D. & Strotmann, A. (2014). The knowledge base and research front of information science 2006-2010: an author cocitation and bibliographic coupling analysis. Journal of the Association for Information Science and Technology, 65(5), 995-1006.   DOI
2 Luong, N. T., Nguyen, T. T., Jung, J. J., & Hwang, D. (2015). Discovering co-author relationship in bibliographic data using similarity measures and random walk model. In Asian Conference on Intelligent Information and Database Systems. Springer, Cham, 127-136.
3 Nam, E. & Park, J. (2014). Factors Influencing Research Collaboration in the Field of Informetrics. Journal of the Korean Society for Library and Information Science, 31(4), 201-227.
4 Newman, M. E. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences, 101(suppl 1), 5200-5205.   DOI
5 Uddin, S., Hossain, L., Abbasi, A., & Rasmussen, K. (2012). Trend and efficiency analysis of co-authorship network. Scientometrics, 90(2), 687-699.   DOI
6 Yan, E. & Ding, Y. (2009). Applying centrality measures to impact analysis: a coauthorship network analysis. Journal of the American Society for Information Science and Technology, 60(10), 2107-2118.   DOI
7 Zhang, C., Bu, Y., Ding, Y., & Xu, J. (2018). Understanding scientific collaboration: Homophily, transitivity, and preferential attachment. Journal of the Association for Information Science and Technology, 69(1), 72-86.   DOI
8 Zhao, D. & Strotmann, A. (2008). Author bibliographic coupling: another approach to citation-based author knowledge network analysis. Proceedings of the American Society for Information Science and Technology, 45(1), 1-10.
9 Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. Proceedings of the International AAAI Conference on Web and Social Media, 3(1), 361-362.
10 Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008.
11 Feng, S. & Kirkley, A. (2020). Mixing patterns in interdisciplinary co-authorship networks at multiple scales. Scientific Reports, 10(1), 1-11.   DOI
12 Glanzel, W. & Schubert, A. (2004). Analysing scientific networks through co-authorship. In Moed, H. F., Glanzel, W., & Schmoch, U. eds. Handbook of Quantitative Science and Technology Research. Springer, Dordrecht, 257-276.
13 Huang, M. H. & Chang, Y. W. (2011). A study of interdisciplinarity in information science: using direct citation and co-authorship analysis. Journal of Information Science, 37(4), 369-378.   DOI
14 Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation, 14(1), 10-25.   DOI
15 Khokhar, D. (2015). Gephi Cookbook. Packt Publishing Ltd.
16 Liu, P. & Xia, H. (2015). Structure and evolution of co-authorship network in an interdisciplinary research field. Scientometrics, 103(1), 101-134.   DOI
17 Kim, D., Kim, K., & Zhu, Y. (2021). A bibliometric analysis of the major Korean journals indexed in 2020 Google Scholar metrics. Korean Society for Information Management, 38(1), 53-69.
18 Li, F., Li, M., Guan, P., Ma, S., & Cui, L. (2015). Mapping publication trends and identifying hot spots of research on Internet health information seeking behavior: a quantitative and co-word biclustering analysis. Journal of Medical Internet Research, 17(3), e3326.
19 Lima, L. H. C., Laender, A. H., Moro, M. M., & De Oliveira, J. P. M. (2020). An analysis of the collaboration network of the international conference on conceptual modeling at the age of 40. Data & Knowledge Engineering, 130, 101866.
20 Liu, X., Bollen, J., Nelson, M. L., & Van de Sompel, H. (2005). Co-authorship networks in the digital library research community. Information Processing & Management, 41(6), 1462-1480.   DOI