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Knowledge in motion: the evolution of HIV/AIDS research

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  • Ryan Light

    (University of Oregon)

  • jimi adams

    (University of Colorado Denver)

Abstract

Many contemporary social and public health problems do not fit neatly into the research fields typically found in universities. With this in mind, researchers and funding agencies have devoted increasing attention to projects that span multiple disciplines. However, comparatively little attention has been paid to how these projects evolve over time. This relative neglect is in part attributable to a lack of theory on the dynamic nature of such projects. In this paper, we describe how research programs can move through various states of integration including disciplinarity, multidisciplinarity, interdisciplinarity and transdisciplinarity. We link this insight to computational techniques—topic models—to explore one of the most vibrant and pressing contemporary research areas—research on HIV/AIDS. Topic models of over 9000 abstracts from two prominent journals illustrate how research on HIV/AIDS has evolved from a high to a lower level of integration. The topic models motivate a more detailed historical analysis of HIV/AIDS research and, together, they highlight the dynamic nature of knowledge production. We conclude by discussing the role of computational social science in dynamic models of interdisciplinarity.

Suggested Citation

  • Ryan Light & jimi adams, 2016. "Knowledge in motion: the evolution of HIV/AIDS research," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1227-1248, June.
    • Handle: RePEc:spr:scient:v:107:y:2016:i:3:d:10.1007_s11192-016-1933-2
    DOI: 10.1007/s11192-016-1933-2
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    References listed on IDEAS

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    1. Grün, Bettina & Hornik, Kurt, 2011. "topicmodels: An R Package for Fitting Topic Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i13).
    2. Jimi Adams & Ryan Light, 2014. "Mapping Interdisciplinary Fields: Efficiencies, Gaps and Redundancies in HIV/AIDS Research," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-13, December.
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    Cited by:

    1. Xie, Qing & Zhang, Xinyuan & Ding, Ying & Song, Min, 2020. "Monolingual and multilingual topic analysis using LDA and BERT embeddings," Journal of Informetrics, Elsevier, vol. 14(3).
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    3. John McLevey & Alexander V. Graham & Reid McIlroy-Young & Pierson Browne & Kathryn S. Plaisance, 2018. "Interdisciplinarity and insularity in the diffusion of knowledge: an analysis of disciplinary boundaries between philosophy of science and the sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 331-349, October.

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