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Intellectual structure evolution of open access research observed through correlation index of keyword centrality

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Abstract

This study captured intellectual structures of open access by time frame using the pathfinder keyword network analysis method. 1998 papers published on Web of Science from 2005 to 2019 were divided into 3-year units, and keyword pathfinder networks were analyzed in five time segments. Thus, this study examined the time series changes of intellectual structure and keyword centrality. In addition, by analyzing the correlation index of keyword centrality between time segments, this study examined how long the similarities of the intellectual structure persisted and how it has changed. As a result, a weak correlation (r = 0.10 ~ r = 0.49) was obtained from the observations in 2005 for 9 years; however, the correlation decreased sharply since 2014 (r = − 0.06 ~ r = 0.00). New research topics have emerged that have not been highlighted in centrality, such as article processing charge, altmetrics, and research data. The scope of research has changed as subjects such as document delivery that showed high centrality initially, disappeared.

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References

  • Alan, P., & Jack, M. (2008). The evolution of the intellectual structure of operations management—1980–2006: A citation/co-citation analysis. Journal of Operations Management, 27(3), 185–202.

    Google Scholar 

  • Al-Khatib, A. (2016). Protecting Authors from Predatory Journals and Publishers. Publishing Research Quarterly, 32, 281–285.

    Article  Google Scholar 

  • Bae, Y. (2015). Analysis of input-performance structure for convergence research between technologies in government R&D projects [cited 2020. 7. 8]. https://scienceon.kisti.re.kr/srch/selectPORSrchReport.do?cn=TRKO201500014110.

  • Bailey, C. W. (2010). Transforming scholarly publishing through open access: A bibliography. Houston, TX: Digital Scholarship.

    Google Scholar 

  • Boukacem-Zeghmouri, C., & Schöpfel, J. (2006). Document supply and open access: an international survey on grey literature. Interlending & Document Supply, 34(3), 96–104. https://doi.org/10.1108/02641610610686012.

    Article  Google Scholar 

  • Chen, C. (2004). Searching for intellectual turning points: Progressive knowledge domain visualization. Proceedings of the National Academy of Sciences, 6, 5303–5310. https://doi.org/10.1073/pnas.0307513100.

    Article  Google Scholar 

  • Chen, X., Chena, J., Wua, D., Xiea, Y., & Li, J. (2016). Mapping the research trends by co-word analysis based on keywords from funded project. Procedia Computer Science, 91, 547–555.

    Article  Google Scholar 

  • Chen, X., Li, J., Sun, X., & Wu, D. (2019). Early identification of intellectual structure based on co-word analysis from research grants. Scientometrics, 121(1), 349–369.

    Article  Google Scholar 

  • Cho, J. (2014). Intellectual structure of the institutional repository field: A co-word analysis. Journal of Information Science, 40, 1–12.

    Article  Google Scholar 

  • Cho, J. (2020). Analysis of open access status of domestic author’s papers published in international journals : Based on highly cited paper. Korean Society for Library and Information Science, 54(1), 325–341.

    Google Scholar 

  • Cho, J. (2018). The trends of media coverage about libraries in Korea: Using semantic network analysis of portal news. Libri, 68(4), 291–300.

    Article  Google Scholar 

  • Cho, J. (2019). Analysis of reading domain of men and women elderly using book lending data. Korean Library and Information Science Society, 50(1), 23–41.

    Article  Google Scholar 

  • Choi, H., Choi, Y., & Nam, S. (2018). Time series analysis of intellectual structure and research trend changes in the field of library and information science: 2003 to 2017. Journal of the Korean society for Information Management, 35(2), 89–114.

    Google Scholar 

  • Department for Business, Innovation & Skills Prime Minister's Office. (2013). G8 Science Ministers Statement London UK. [cited 2020. 6. 15] https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/206801/G8_Science_Meeting_Statement_12_June_2013.pdf.

  • Ding, Y., Chowdhury, G., & Foo, S. (1999). Mapping the intellectual structure of information retrieval studies: An author co-citation analysis, 1987–1997. Journal of Information Science, 25(1), 67–78.

    Article  Google Scholar 

  • González-Valiente, C. L., Pacheco-Mendoza, J., & Arencibia-Jorge, R. (2016). A review of altmetrics as an emerging discipline for research evaluation. Learned Publishing, 29(4), 229–238.

    Article  Google Scholar 

  • Heo, G., & Song, M. (2013). Examining the intellectual structure of a medical informatics journal with author co-citation Analysis and co-word analysis. Journal of the Korean Society for Information Management, 30(2), 207–225.

    Article  Google Scholar 

  • Kellersohn, A., Meyer, T., Mittermaier, B., & Schaeffler, H. (2011). Between pay-per-view and "big deal"—Licensing electronic information in Germany. ZEITSCHRIFT FUR BIBLIOTHEKSWESEN UND BIBLIOGRAPHIE, 58, 120–130.

    Article  Google Scholar 

  • Kim, K. (2014). Examining of knowledge structure of sports sociology through social network analysis of authors co-citation: Analysis on Journal of Sociology of Sport (KJSS). Korean Society for the Sociology of Sport, 27(4), 109–137.

    Article  Google Scholar 

  • Kwak, S., & Chung, E. (2012). Domain analysis on economics by utilizing co-citation analysis of multiple authorship. Journal of the Korean Society for Information Management, 29(1), 115–134.

    Article  Google Scholar 

  • Lee, J. (2006a). A study on the network generation methods for examining the intellectual structure of knowledge domains. Journal of the Korean Society for Library and Information Science, 40(2), 333–355.

    Article  Google Scholar 

  • Lee, J. (2006b). A novel clustering method for examining and analyzing the intellectual structure of a scholarly field. Korea Society for Information management, 23(4), 215–231.

    Article  Google Scholar 

  • Lee, J. (2006c). Centrality measures for bibliometric network analysis. Journal of the Korean Society For Library And Information Science, 40(3), 191–214.

    Article  Google Scholar 

  • Lee, J. (2013). A comparison study on the weighted network centrality measures of tnet and WNET. Journal of the Korean society for information management, 30(4), 241–264.

    Article  Google Scholar 

  • Leeuwen, T. N., Tatum, C., & Wouters, P. F. (2018). Exploring possibilities to use bibliometric data to monitor gold open access publishing at the national level. JASIST, 69(9), 1161–1173.

    Google Scholar 

  • McGlashan, D., & Hadley, K. (2019). Adapting to a transformative future: Open Access and PlanS. [cited 2019. 12. 8] https://www.jstage.jst.go.jp/static/files/ja/pub_20190621_Seminar01.pdf.

  • Miguel, S., Oliveira, E. F. T., & Grácio, M. C. C. (2016). Scientific production on open access: A worldwide bibliometric analysis in the academic and scientific context. Publications, 4, 1–15.

    Article  Google Scholar 

  • National Institutes of Health. Request for Information: NIH Public Access Policy. [cited 2015. 8. 15] https://publicaccess.nih.gov/comments.htm.

  • OA2020. (2019). OA2020 progress report. [cited 2019. 12. 6.] https://oa2020.org/progress-report-nov2019/.

  • Onyancha, O. B. (2016). Open research data in sub-Saharan Africa: A bibliometric study using the data citation index. Publishing Research Quarterly, 32, 227–247.

    Article  Google Scholar 

  • Park, E. (2007). Perspectives on access to electronic journals for long-term preservation. Serials Review, 33(13), 22–25.

    Article  Google Scholar 

  • Park, J., & Jeong, D. (2013). A study on the intellectual structure of library and information science in Korea by author bibliographic coupling analysis. Journal of the Korean Society for Information Management, 30(4), 31–59.

    Article  Google Scholar 

  • Pavan, C., & Barbosa, M. C. (2018). Article processing charge (APC) for publishing open access articles: The Brazilian scenario. Scientometrics, 117(2), 805–823.

    Article  Google Scholar 

  • Pisoschi, A. M., & Pisoschi, C. G. (2016). Is open access the solution to increase the impact of scientific journals? Scientometrics, 109, 1075–1095.

    Article  Google Scholar 

  • Poplašen, L. M., & Grgić, I. H. (2016). Altmetric and bibliometric scores: Does open access matter? Qualitative and Quantitative Methods in Libraries, 5, 251–460.

    Google Scholar 

  • RCUK Policy on Open Access and Supporting Guidance. [cited 2015. 8. 15]. https://www.ukri.org/files/legacy/documents/rcukopenaccesspolicy-pdf.

  • Rodrigues, R. S. R., Taga, V., & Passos, M. F. (2016). Research articles about open access indexed by scopus: A content analysis. Publications., 4(4), 31. https://doi.org/10.3390/publications4040031.

    Article  Google Scholar 

  • Rokaya, E., Atlam, M., Fuketa, T. C., & Dorji, J. I. (2008). Aoe Ranking of field association terms using co-word analysis. Information Processing & Management, 44(2), 738–755.

    Article  Google Scholar 

  • Ronda-Pupo, G. A., & Guerras-Martin, L. Á. (2012). Dynamics of the evolution of the strategy concept 1962–2008: A co-word analysis. Strategic Management Journal, 33(2), 162–188.

    Article  Google Scholar 

  • SCOAP3. https://scoap3.org/news102/.

  • Segado-Boj, F., Martín-Quevedo, J., & Prieto-Gutiérrez, J. J. (2018). Attitudes toward open access, open peer review, and altmetrics among contributors to spanish scholarly journals. Journal of Scholarly Publishing, 50(1), 48–70.

    Article  Google Scholar 

  • Suh, S., & Jeong, E. (2013). Domain analysis on the field of open access by co-word analysis. Korean Biblia Society for Library and Information Science, 24(1), 207–228.

    Article  Google Scholar 

  • Szell, M., Lambiotte, R., & Thurner, S. (2010). Multirelational organization of large-scale social networks in an online world. Proceedings of the National Academy of Sciences of the United States of America, 107(31), 13636–13641.

    Article  Google Scholar 

  • The office of Science and Technology Policy. (2013). Increasing access to the results of federally funded scientific research. [cited 2015. 8. 15]. https://www.whitehouse.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf.

  • White, H. D. (2003). Pathfinder networks and author cocitation analysis: A remapping of paradigmatic information scientists. Journal of the American Society for Information Science & Technology, 54(5), 423–434.

    Article  Google Scholar 

  • Yiotis, K. (2005). The open access initiative: A New paradigm for scholarly communications. Information Technology and Libraries, 24(4), 157–162. https://doi.org/10.6017/ital.v24i4.3378.

    Article  Google Scholar 

  • Zhao, R., & Wu, S. (2014). Study on themes and authors’ influence of open access in China. Scientometrics, 101, 1165–1177.

    Article  Google Scholar 

Download references

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Cho, J. Intellectual structure evolution of open access research observed through correlation index of keyword centrality. Scientometrics 125, 2617–2635 (2020). https://doi.org/10.1007/s11192-020-03682-4

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