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A longitudinal study of intellectual cohesion in digital humanities using bibliometric analyses

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  • Muh-Chyun Tang

    (National Taiwan University)

  • Yun Jen Cheng

    (National Taiwan University)

  • Kuang Hua Chen

    (National Taiwan University)

Abstract

As digital humanities continues to expand and become more inclusive, little is known about the extent to which its knowledge is integrated. A bibliometric analysis of published literature in digital humanities was conducted to examine the degree of its intellectual cohesion over time (1989–2014). Co-authorship, article co-citation, and bibliographic coupling networks were generated so SNA based cohesion analysis can be applied. Modularity maximization partition was also performed to both co-citation and “author bibliographic coupling” networks to identify main research interests manifested in the literature. The results show that, as publications in digital humanities continue to grow, its diversity and coherence, two hallmarks of interdisciplinarity, have shown signs of becoming more robust. The co-author network, however, remained rather fragmented, with collaboration mainly limited by language and geographic boundaries. The domain specific practices in digital humanities that might contribute to such fragmentation was discussed.

Suggested Citation

  • Muh-Chyun Tang & Yun Jen Cheng & Kuang Hua Chen, 2017. "A longitudinal study of intellectual cohesion in digital humanities using bibliometric analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 985-1008, November.
    • Handle: RePEc:spr:scient:v:113:y:2017:i:2:d:10.1007_s11192-017-2496-6
    DOI: 10.1007/s11192-017-2496-6
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    References listed on IDEAS

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    1. Ismael Rafols & Martin Meyer, 2010. "Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 263-287, February.
    2. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    3. Loet Leydesdorff & Alkim Almila Akdag Salah, 2010. "Maps on the basis of the Arts & Humanities Citation Index: The journals Leonardo and Art Journal versus “digital humanities” as a topic," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(4), pages 787-801, April.
    4. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    5. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    6. James Moody & Douglas R. White, 2000. "Structural Cohesion and Embeddedness: A Hierarchical Conception of Social Groups," Working Papers 00-08-049, Santa Fe Institute.
    7. Alan L. Porter & Alex S. Cohen & J. David Roessner & Marty Perreault, 2007. "Measuring researcher interdisciplinarity," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(1), pages 117-147, July.
    8. Jon Leefmann & Clément Levallois & Elisabeth Hildt, 2016. "Neuroethics 1995-2012. A bibliometric analysis of the guiding themes of an emerging research field," Post-Print hal-02313439, HAL.
    9. Peng Liu & Haoxiang Xia, 2015. "Structure and evolution of co-authorship network in an interdisciplinary research field," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 101-134, April.
    10. Francisco José Acedo & Carmen Barroso & Cristóbal Casanueva & José Luis Galán, 2006. "Co‐Authorship in Management and Organizational Studies: An Empirical and Network Analysis," Journal of Management Studies, Wiley Blackwell, vol. 43(5), pages 957-983, July.
    11. Katherine W. McCain, 1990. "Mapping authors in intellectual space: A technical overview," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 433-443, September.
    12. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    13. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    14. Clément Levallois & John A. Clithero & Paul Wouters & Ale Smidts & Scott A. Huettel, 2012. "Translating upwards : linking the neural and social sciences via neuroeconomics," Post-Print hal-02313160, HAL.
    15. Anton J. Nederhof, 2006. "Bibliometric monitoring of research performance in the Social Sciences and the Humanities: A Review," Scientometrics, Springer;Akadémiai Kiadó, vol. 66(1), pages 81-100, January.
    16. Alan L. Porter & Ismael Rafols, 2009. "Is science becoming more interdisciplinary? Measuring and mapping six research fields over time," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 719-745, December.
    17. Wagner, Caroline S. & Roessner, J. David & Bobb, Kamau & Klein, Julie Thompson & Boyack, Kevin W. & Keyton, Joann & Rafols, Ismael & Börner, Katy, 2011. "Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature," Journal of Informetrics, Elsevier, vol. 5(1), pages 14-26.
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    Cited by:

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    2. Moshe Blidstein & Maayan Zhitomirsky-Geffet, 2022. "Towards a new generic framework for citation network generation and analysis in the humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4275-4297, July.
    3. Wei‐Min Fan & Wei Jeng & Muh‐Chyun Tang, 2023. "Using data citation to define a knowledge domain: A case study of the Add‐Health dataset," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(1), pages 81-98, January.
    4. Marcia Lei Zeng & Chris Alen Sula & Karen F. Gracy & Eero Hyvönen & Vânia Mara Alves Lima, 2022. "JASIST special issue on digital humanities (DH)," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(2), pages 143-147, February.
    5. José Alberto Molina & David Iñiguez & Gonzalo Ruiz & Alfonso Tarancón, 2018. "The Nobel Prize in Economics: individual or collective merits?," Boston College Working Papers in Economics 966, Boston College Department of Economics.
    6. Jan Luhmann & Manuel Burghardt, 2022. "Digital humanities—A discipline in its own right? An analysis of the role and position of digital humanities in the academic landscape," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(2), pages 148-171, February.
    7. Fan, Yangliu & Lehmann, Sune & Blok, Anders, 2022. "Extracting the interdisciplinary specialty structures in social media data-based research: A clustering-based network approach," Journal of Informetrics, Elsevier, vol. 16(3).

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