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Topic Modeling based Interdisciplinarity Measurement in the Informatics Related Journals
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Topic Modeling based Interdisciplinarity Measurement in the Informatics Related Journals
Jin, Seol A; Song, Min;
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This study has measured interdisciplinarity using a topic modeling, which automatically extracts sub-topics based on term information appeared in documents group unlike the traditional top-down approach employing the references and classification system as a basis. We used titles and abstracts of the articles published in top 20 journals for the past five years by the 5-year impact factor under the category of 'Information & Library Science' in JCR 2013. We applied 'Discipline Diversity' and 'Network Coherence' as factors in measuring interdisciplinarity; 'Shannon Entropy Index' and 'Stirling Diversity Index' were used as indices to gauge diversity of fields while topic network's average path length was employed as an index representing network cohesion. After classifying the types of interdisciplinarity with the diversity and cohesion indices produced, we compared the topic networks of journals that represent each type. As a result, we found that the text-based diversity index showed different ranking when compared to the reference-based diversity index. This signifies that those two indices can be utilized complimentarily. It was also confirmed that the characteristics and interconnectedness of the sub-topics dealt with in each journal can be intuitively understood through the topic networks classified by considering both the diversity and cohesion. In conclusion, the topic modeling-based measurement of interdisciplinarity that this study proposed was confirmed to be applicable serving multiple roles in showing the interdisciplinarity of the journals.
textmining;topic modeling;scholarly journal;interdisciplinary;diversity index;
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강범일, 이재윤 (2014). 트위터 관련 연구에 대한 계량정보학적 분석. 정보관리학회지, 31(3), 293-311., Beomil, & Lee, Jae Yun (2014). A bibliometric analysis on twitter research. Journal ofthe Korean Society for Information Management, 31(3), 293-311. crossref(new window)

박소윤 (2013). 문헌정보학 분야의 학제성과 연구 영향력에 관한 연구. 석사학위논문, 이화여자대학교 대학원, 문헌정보학과.(Park, So Yoon (2013). A study on interdisciplinarity and research impact in the field of libraryand information science. Master's Thesis. The Graduate School of Ewha Womans University. Department of Library and Information Science.)

박자현, 송민 (2013). 토픽모델링을 활용한 국내 문헌정보학 연구동향 분석. 정보관리학회지, 30(1), 7-32., Ja-Hyun, & Song, Min (2013). A study on the research trends in library & informationscience in Korea using topic modeling. Journal of the Korean Society for Information Management, 30(1), 7-32. crossref(new window)

Adams, J., Jackson, L., & Marshall, S. (2007). Bibliometric analysis of interdisciplinary research. Report to Higher Education Funding Council for England.

Bache, K., Newman, D., & Smyth, P. (2013). Text-based measures of document diversity. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 23-31. ACM.

Bordons, M., Morillo, F., & Gomez, I. (2004). Analysis of cross-disciplinary research through bibliometric tools. In H. F. Moed, W. Glanzel & U. Schmoch (Eds.), Handbook of quantitative science and technology research (pp. 437-456). Dordrecht: Kluwer.

Brillouin, L. (1956). Science and information theory. New York: Academic Press.

Carayol, N., & Thi, T. U. N. (2005). Why do academic scientists engage in interdisciplinary research?. Research evaluation, 14(1), 70-79. crossref(new window)

Chua, A. Y., & Yang, C. C. (2008). The shift towards multi‐disciplinarity in information science. Journal of the American Society for Information Science and Technology, 59(13), 2156-2170. crossref(new window)

Cronin, B., & Meho, L. I. (2008). The shifting balance of intellectual trade in information studies. Journal of the American Society for Information Science and Technology, 59(4), 551-564. crossref(new window)

Ding, Y., Liu, X., Guo, C., & Cronin, B. (2013). The distribution of references across texts: Some implications for citation analysis. Journal of Informetrics, 7(3), 583-592. crossref(new window)

Herring, S. D. (1999). The value of interdisciplinarity: A study based on the design of Internet search engines. Journal of the American Society for Information Science, 50(4), 358-365.<358::aid-asi14>;2-7 crossref(new window)

Lariviere, V., & Gingras, Y. (2010). On the relationship between interdisciplinarity and scientific impact. Journal of the American Society for Information Science and Technology, 61(1), 126-131. crossref(new window)

Levitt, J. M., & Thelwall, M. (2009). The most highly cited Library and Information Science articles: Interdisciplinarity, first authors and citation patterns. Scientometrics, 78(1), 45-67. crossref(new window)

Leydesdorff, L., & Rafols, I. (2011). Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations. Journal of Informetrics, 5(1), 87-100. crossref(new window)

Leydesdorff, L., Rafols, I., & Chen, C. (2013). Interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal-journal citations. Journal of the American Society for Information Science and Technology, 64(12), 2573-2586. crossref(new window)

Mann, G. S., Mimno, D., & McCallum, A. (2006). Bibliometric impact measures leveraging topic analysis. Proceedings of the 6th ACM/IEEE-CS Joint Conference, 65-74. IEEE.

Moravcsik, M. J., & Murugesan, P. (1975). Some results on the function and quality of citations. Social Studies of Science, 5(1), 86-92. crossref(new window)

Morillo, F., Bordons, M., & Gomez, I. (2001). An approach to interdisciplinarity through bibliometric indicators. Scientometrics, 51(1), 203-222. crossref(new window)

Morillo, F., Bordons, M., & Gomez, I. (2003). Interdisciplinarity in science: A tentative typology of disciplines and research areas. Journal of the American Society for Information Science and Technology, 54(13), 1237-1249. crossref(new window)

National Academies (2004). Facilitating interdisciplinary research. Committee on Science, Engineering, and Public Policy (Cosepup) & Committee on Facilitating Interdisciplinary Research. Washington, D.C.: The National Academies Press.

Nichols, L. G. (2014). A topic model approach to measuring interdisciplinarity at the National Science Foundation. Scientometrics, 100(3), 1-14. crossref(new window)

Organisation for Economic Cooperation and Development (OECD). (1998). Interdisciplinarity in science and technology. Directorate for science. technology and industry. Paris: OECD.

Porter, A. L., & Chubin, D. E. (1985). An indicator of cross-disciplinary research. Scientometrics, 8(3), 161-176. crossref(new window)

Porter, A. L., & Rafols, I. (2009). Is science becoming more interdisciplinary? Measuring and mapping six research fields over time. Scientometrics, 81(3), 719-745. crossref(new window)

Prebor, G. (2010). Analysis of the interdisciplinary nature of library and information science. Journal of Librarianship and Information Science, 42(4), 256-267. crossref(new window)

Qin, J., Lancaster, F. W., & Allen, B. (1997). Types and levels of collaboration in interdisciplinary research in the sciences. Journal of the American Society for information Science, 48(10), 893-916.<893::aid-asi5>;2-x crossref(new window)

Rafols, I., Leydesdorff, L., O'Hare, A., Nightingale, P., & Stirling, A. (2012). How journal rankings can suppress interdisciplinary research: A comparison between innovation studies and business & management. Research Policy, 41(7), 1262-1282. crossref(new window)

Rafols, I., & Meyer, M. (2010). Diversity and network coherence as indicators of interdisciplinarity: Case studies in bionanoscience. Scientometrics, 82(2), 263-287. crossref(new window)

Rinia, E. J., van Leeuwen, T. N., & van Raan, A. F. (2002). Impact measures of interdisciplinary research in physics. Scientometrics, 53(2), 241-248. crossref(new window)

Schummer, J. (2004). Multidisciplinarity, interdisciplinarity, and patterns of research collaboration in nanoscience and nanotechnology. Scientometrics, 59(3), 425-465. crossref(new window)

Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27, 379-423 and 623-656. crossref(new window)

Simpson, E. H. (1949). Measurement of diversity. Nature, 163, 688. crossref(new window)

Stirling, A. (1998). On the economics and analysis of diversity. SPRU Electronic Working Papers. Retrieved from

Stirling, A. (2007). A general framework for analysing diversity in science, technology and society. Journal of the Royal Society Interface, 4(15), 707-719. crossref(new window)

Tang, R. (2004). Evolution of the interdisciplinary characteristics of information and library science. Proceedings of the American Society for Information Science and Technology, 41(1), 54-63.

Yegros-Yegros, A., Amat, C. B., D'Este, P., Porter, A. L., & Rafols, I. (2010). Does interdisciplinary research lead to higher scientific impact. In STI Indicators Conference, Leiden.