Abstract
Author co-citation analysis (ACA) is a well-known and frequently-used method to exhibit the academic researchers and the professional field sketch according to co-citation relationships between authors in an article set. However, visualizing subtle examination is limited because only author co-citation information is required in ACA. The proposed method, called modified author co-citation analysis (MACA), exploits author co-citation relationship, citations published time, citations published carriers, and citations keywords, to construct MACA-based co-citation matrices. According to the results of our experiments: (1) MACA shows a good clustering result with more delicacy and more clearness; (2) more information involved in co-citation analysis performs good visual acuity; (3) in visualization of co-citation network produced by MACA, the points in different categories have far more distance, and the points indicating authors in the same category are closer together. As a result, the proposed MACA is found that more detailed and subtle information of a knowledge domain analyzed can be obtained, compared to ACA.
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Notes
Its name was Journal of the American Society for Information Science before 2001. Nevertheless, this journal changed its name to Journal of the Association for Information Science and Technology in 2014.
This is the URL of Y. Ding’s personal website: http://info.ils.indiana.edu/~dingying.
This is the URL of L. Bornmann’s personal website: http://www.lutz-bornmann.de.
References
Ahlgren, P., Jarneving, B., & Rousseau, R. (2003). Requirements for a citation similarity measure, with special reference to Pearson`s correlation coefficient. Journal of the American Society for Information Science and Technology, 54(6), 550–560.
An, L., Zhang, J., & Yu, C. (2011). The visual subject analysis of library and information science journals with self-organizing map. Knowledge Organization, 38(4), 299–320.
Bensman, S. J. (2004). Pearson’s r and author co-citation analysis: A commentary on the controversy. Journal of the American Society for Information Science and Technology, 55(10), 935.
Bianchini, M., Gori, M., & Scarselli, F. (2005). Inside PageRank. ACM Transactions on Internet Technology, 5(1), 92–128.
Bornmann, L., & Daniel, H. D. (2008). What do citation count measure? A review of studies on citing behavior. Journal of Documentation, 64, 45–80.
Brooks, T. A. (1985). Private acts and public objects: An investigation of citer motivations. Journal of the American Society for Information Science, 36(4), 223–229.
Bu, Y., Liu, T., & Huang, B. (2015). Exploration on research of improving traditional author co-citation analysis: A novel author co-citation analysis method combining with publishing time of cited papers. Library and Information Knowledge, 32(6), 89–97.
Case, D. O., & Miller, J. (2011). Do bibliometricians cite differently from other scholars? Journal of the American Society for Information Science and Technology, 62(3), 421–432.
Chen, C. (1999). Visualizing semantic spaces and author co-citation networks in digital libraries. Information Processing and Management, 35(3), 401–420.
Cothill, C. A., Rogers, E. M., & Mills, T. (1989). Co-citation analysis of the scientific literature of innovation research traditions. Science Communication, 11(2), 181–208.
Davis, P. (2004). Information-seeking behavior of chemists: A transaction log analysis of referral URLs. Journal of the American Society for Information Science and Technology, 55(4), 326–332.
Ding, Y. (2011). Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks. Journal of Informetrics, 5(1), 187–203.
Ding, Y., Chowdhury, G., & Foo, S. (2000). Journal as markers of intellectual space: Journal co-citation analysis of information retrieval area, 1987–1997. Scientometrics, 47(1), 55–73.
Ding, Y., Liu, X., & Guo, C. (2013). The distribution of references across texts: Some implications for citation analysis. Journal of Informetrics, 7(3), 583–592.
Ding, Y., Yan, E., Frazho, A., & Caverlee, J. (2009). PageRank for ranking authors in co-citation networks. Journal of the Association for Information Science and Technology, 60(11), 2229–2243.
Egghe, L. (2009). New relations between similarity measures for vectors based on vector norms. Journal of the American Society for Information Science and Technology, 60(2), 232–239.
Eom, S. (1999). Decision support systems research: Current state and trends. Industrial Management and Data Systems, 99(5), 213–221.
Eom, S. (2008a). Author co-citation analysis: Quantitative methods for mapping the intellectual structure of an academic discipline. Hershey, NY: Information Science Reference.
Eom, S. (2008b). All author co-citation analysis and first author co-citation analysis: A comparative empirical investigation. Journal of Informetrics, 2(1), 53–64.
Hartley, J. (2008). Academic writing and publishing: A practical guide. New York: Routledge.
Jeong, Y. K., Song, M., & Ding, Y. (2014). Content-based author co-citation analysis. Journal of Informetrics, 8(1), 197–211.
Kaufman, L., & Rousseeuw, P. J. (1990). Finding groups in data: An introduction to cluster analysis. New York: John Wiley and Sons.
Leydesdorff, L., & Vaughan, L. (2006). Co-occurrence matrices and their applications in information science: Extending ACA to the web environment. Journal of the American Society for Information Science and Technology, 57(12), 1616–1628.
Li, J., & Gong, J. (2010). Frontier and trend analysis of information science research based on JASIST. Research in Library Science, 3, 2–6.
Liu, L., Xuan, Z., Dang, Z., Guo, Q., & Wang, Z. (2007). Weighted network properties of Chinese nature science basic research. Physica A-Statistical Mechanics and Its Applications, 377(1), 302–314.
McCain, K. W. (1990). Mapping authors in intellectual space: a technical overview. Journal of the American Society for Information Science, 41(6), 433–443.
McCain, K. W. (1991). Mapping economics through the journal literature: An experiment in journal co-citation analysis. Journal of the American Society for Information Science, 42(4), 290–296.
Mêgnigbêto, E. (2013). Controversies arising from which similarity measures can be used in co-citation analysis. Malaysian Journal of Library and Information Science, 18(2), 25–31.
Moya-Anegón, S. G., Vargas-Quesada, B., Chinchilla-Rodríguez, Z., Corera-Álvarez, E., Munoz-Fernández, F. J., & Herrero-Solana, V. (2007). Visualizing the marrow of science. Journal of the American Society for Information Science and Technology, 58(14), 2167–2179.
Park, H., & Park, M. (2014). Cancer information-seeking behaviors and information needs among Korean Americans in the online community. Journal of Community Health, 39(2), 213–220.
Persson, O. (2001). All author citations versus first author citations. Scientometrics, 50(2), 339–344.
Rousseau, R., & Zuccala, A. (2004). A classification of author co-citations: Definitions and search strategies. Journal of the American Society for Information Science, 55(6), 513–529.
Schneider, J. W., & Larsen, B. (2009). A comparative study of first and all-author co-citation counting, and two different matrix generation approaches applied for author co-citation analyses. Scientometrics, 80(1), 103–130.
Swandon, D. (1977). Critique of psychic energy as an explanatory concept. Journal of the American Psychoanalytic Association, 25(3), 603–633.
Swanson, D. (1960). Searching natural language text by computer. Science, 132, 1099–1104.
Swanson, D. (1979). XMARC: A system for experimental indexing and searching of MARC records. Journal of Education for Librarianship, 20(2), 91–106.
Swanson, D., Smalheiser, N., & Bookstein, A. (2001). Information discovery from complementary literatures: Categorizing viruses as potential weapons. Journal of the American Society for Information Science and Technology, 52(10), 797–812.
Tsay, M. Y. (2011). The subject structure of randomized controlled trials: An author co-citation analysis. In Noyons, E., Ngulube, P., & Leta, J. (Eds.). Proceedings of ISSI 2011—The 13th international conference on scientometrics and informetrics. Durban, pp. 1067–1069.
White, H. D. (2003a). Author co-citation analysis and Pearson’s r. Journal of the American Society for Information Science and Technology, 54(13), 1250–1259.
White, H. D. (2003b). Pathfinder networks and author co-citation analysis: A remapping of paradigmatic information scientists. Journal of the American Society for Information Science and Technology, 54(5), 423–434.
White, H. D., & Griffith, B. C. (1981). Author co-citation: A literature measure of intellectual structure. Journal of the American Society for Information Science, 32(3), 163–171.
White, H. D., & McCain, K. W. (1998). Visualizing a discipline: An author co-citation analysis of information science 1972–1995. Journal of the American Society for Information Science, 49(4), 327–335.
Wu, Y., Fu, T., & Chiu, D. (2014). Generalized preferential attachment considering aging. Journal of Informetrics, 8(3), 650–658.
Yang, J. (2013). The Library and Information Science research hotpot perspective based on JASIST. Library Work and Study, 2, 22–25.
Zhao, D. (2006). Towards all-author co-citation analysis. Information Processing and Management, 42(6), 1578–1591.
Zhao, D., & Logan, E. (2002). Citation analysis using scientific publications on the web as data source: A case study in the XML research area. Scientometrics, 54(2), 449–472.
Zhao, D., & Strotmann, A. (2008). Comparing all-author and first-author co-citation analyses of information science. Journal of Informetrics, 2(3), 229–239.
Acknowledgments
The authors would like to thank two research assistants in our group, Binglu Wang and Chengyue Gong, for their kind help on part of data collections and preliminary author-filtering. We are also very grateful for the constructive comments and helpful suggestions from the anonymous reviewers and the editor in chief of Scientometrics, Dr. Wolfgang Glänzel.
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Bu, Y., Liu, Ty. & Huang, Wb. MACA: a modified author co-citation analysis method combined with general descriptive metadata of citations. Scientometrics 108, 143–166 (2016). https://doi.org/10.1007/s11192-016-1959-5
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DOI: https://doi.org/10.1007/s11192-016-1959-5