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The shifting sands of disciplinary development: Analyzing North American Library and Information Science dissertations using latent Dirichlet allocation

Author

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  • Cassidy R. Sugimoto
  • Daifeng Li
  • Terrell G. Russell
  • S. Craig Finlay
  • Ying Ding

Abstract

This work identifies changes in dominant topics in library and information science (LIS) over time, by analyzing the 3,121 doctoral dissertations completed between 1930 and 2009 at North American Library and Information Science programs. The authors utilize latent Dirichlet allocation (LDA) to identify latent topics diachronically and to identify representative dissertations of those topics. The findings indicate that the main topics in LIS have changed substantially from those in the initial period (1930–1969) to the present (2000–2009). However, some themes occurred in multiple periods, representing core areas of the field: library history occurred in the first two periods; citation analysis in the second and third periods; and information‐seeking behavior in the fourth and last period. Two topics occurred in three of the five periods: information retrieval and information use. One of the notable changes in the topics was the diminishing use of the word library (and related terms). This has implications for the provision of doctoral education in LIS. This work is compared to other earlier analyses and provides validation for the use of LDA in topic analysis of a discipline.

Suggested Citation

  • Cassidy R. Sugimoto & Daifeng Li & Terrell G. Russell & S. Craig Finlay & Ying Ding, 2011. "The shifting sands of disciplinary development: Analyzing North American Library and Information Science dissertations using latent Dirichlet allocation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(1), pages 185-204, January.
  • Handle: RePEc:bla:jamist:v:62:y:2011:i:1:p:185-204
    DOI: 10.1002/asi.21435
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    1. Staša Milojević & Cassidy R. Sugimoto & Erjia Yan & Ying Ding, 2011. "The cognitive structure of Library and Information Science: Analysis of article title words," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1933-1953, October.
    2. Yosuke Miyata & Emi Ishita & Fang Yang & Michimasa Yamamoto & Azusa Iwase & Keiko Kurata, 2020. "Knowledge structure transition in library and information science: topic modeling and visualization," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 665-687, October.
    3. Beibei Hu & Xianlei Dong & Chenwei Zhang & Timothy D. Bowman & Ying Ding & Staša Milojević & Chaoqun Ni & Erjia Yan & Vincent Larivière, 2015. "A lead-lag analysis of the topic evolution patterns for preprints and publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(12), pages 2643-2656, December.
    4. Nikoleta E. Glynatsi & Vincent A. Knight, 2021. "A bibliometric study of research topics, collaboration, and centrality in the iterated prisoner’s dilemma," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-12, December.
    5. Wen-Yau Cathy Lin, 2012. "Research status and characteristics of library and information science in Taiwan: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 7-21, July.
    6. Yi Bu & Binglu Wang & Win-bin Huang & Shangkun Che & Yong Huang, 2018. "Using the appearance of citations in full text on author co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 275-289, July.
    7. Erjia Yan, 2014. "Topic-based Pagerank: toward a topic-level scientific evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 407-437, August.
    8. John Rigby & Barbara Jones, 2020. "Bringing the doctoral thesis by published papers to the Social Sciences and the Humanities: A quantitative easing? A small study of doctoral thesis submission rules and practice in two disciplines in ," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1387-1409, August.
    9. Manika Lamba & Margam Madhusudhan, 2019. "Mapping of topics in DESIDOC Journal of Library and Information Technology, India: a study," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 477-505, August.
    10. Chaoqun Ni & Cassidy R. Sugimoto & Blaise Cronin, 2013. "Visualizing and comparing four facets of scholarly communication: producers, artifacts, concepts, and gatekeepers," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1161-1173, March.
    11. Yu-Wei Chang, 2018. "Examining interdisciplinarity of library and information science (LIS) based on LIS articles contributed by non-LIS authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1589-1613, September.
    12. Sabina-Cristiana NECULA & Catalin STRIMBEI, 2019. "Identifying Software Complexity Topics with Latent Dirichlet Allocation on Design Patterns," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 23(4), pages 5-16.
    13. Ebadi, Ashkan & Tremblay, Stéphane & Goutte, Cyril & Schiffauerova, Andrea, 2020. "Application of machine learning techniques to assess the trends and alignment of the funded research output," Journal of Informetrics, Elsevier, vol. 14(2).
    14. Zuo, Zhiya & Zhao, Kang & Ni, Chaoqun, 2019. "Standing on the shoulders of giants?—Faculty hiring in information schools," Journal of Informetrics, Elsevier, vol. 13(1), pages 341-353.
    15. Carlos G. Figuerola & Francisco Javier García Marco & María Pinto, 2017. "Mapping the evolution of library and information science (1978–2014) using topic modeling on LISA," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1507-1535, September.
    16. Chen, Guo & Xiao, Lu, 2016. "Selecting publication keywords for domain analysis in bibliometrics: A comparison of three methods," Journal of Informetrics, Elsevier, vol. 10(1), pages 212-223.
    17. Bo Wang & Shengbo Liu & Kun Ding & Zeyuan Liu & Jing Xu, 2014. "Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis: a case study in LTE technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 685-704, October.
    18. McLevey, John & McIlroy-Young, Reid, 2017. "Introducing metaknowledge: Software for computational research in information science, network analysis, and science of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 176-197.
    19. Abhijit Thakuria & Dipen Deka, 2024. "A decadal study on identifying latent topics and research trends in open access LIS journals using topic modeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 3841-3869, July.
    20. Yan, Erjia, 2014. "Research dynamics: Measuring the continuity and popularity of research topics," Journal of Informetrics, Elsevier, vol. 8(1), pages 98-110.
    21. Pin Li & Guoli Yang & Chuanqi Wang, 2019. "Visual topical analysis of library and information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1753-1791, December.
    22. Kim, Min Sung & Kim, Junghwan & Kim, Seongcheol, 2023. "Korea's leadership in 5G and beyond: Footprints and futures," Telecommunications Policy, Elsevier, vol. 47(8).
    23. Andrei P Kirilenko & Svetlana Stepchenkova, 2018. "Tourism research from its inception to present day: Subject area, geography, and gender distributions," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-20, November.
    24. Qian-Jin Zong & Hong-Zhou Shen & Qin-Jian Yuan & Xiao-Wei Hu & Zhi-Ping Hou & Shun-Guo Deng, 2013. "Doctoral dissertations of Library and Information Science in China: A co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 781-799, February.
    25. Sarah Tiba & Frank J. van Rijnsoever & Marko P. Hekkert, 2019. "Firms with benefits: A systematic review of responsible entrepreneurship and corporate social responsibility literature," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 26(2), pages 265-284, March.

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