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Quantitative Analysis of the Interdisciplinarity of Applied Mathematics

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  • Zheng Xie
  • Xiaojun Duan
  • Zhenzheng Ouyang
  • Pengyuan Zhang

Abstract

The increasing use of mathematical techniques in scientific research leads to the interdisciplinarity of applied mathematics. This viewpoint is validated quantitatively here by statistical and network analysis on the corpus PNAS 1999–2013. A network describing the interdisciplinary relationships between disciplines in a panoramic view is built based on the corpus. Specific network indicators show the hub role of applied mathematics in interdisciplinary research. The statistical analysis on the corpus content finds that algorithms, a primary topic of applied mathematics, positively correlates, increasingly co-occurs, and has an equilibrium relationship in the long-run with certain typical research paradigms and methodologies. The finding can be understood as an intrinsic cause of the interdisciplinarity of applied mathematics.

Suggested Citation

  • Zheng Xie & Xiaojun Duan & Zhenzheng Ouyang & Pengyuan Zhang, 2015. "Quantitative Analysis of the Interdisciplinarity of Applied Mathematics," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-11, September.
    • Handle: RePEc:plo:pone00:0137424
    DOI: 10.1371/journal.pone.0137424
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    References listed on IDEAS

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    1. Zheng Xie & Zhenzheng Ouyang & Pengyuan Zhang & Dongyun Yi & Dexing Kong, 2015. "Modeling the Citation Network by Network Cosmology," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-13, March.
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    3. Xie, Zheng & Dong, Enming & Li, Jianping & Kong, Dexing & Wu, Ning, 2014. "Potential links by neighbor communities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 244-252.
    4. Xie, Zheng & Zhu, Jiang & Kong, Dexing & Li, Jianping, 2015. "A random geometric graph built on a time-varying Riemannian manifold," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 492-498.
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    Citations

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    Cited by:

    1. Zuo, Zhiya & Zhao, Kang, 2018. "The more multidisciplinary the better? – The prevalence and interdisciplinarity of research collaborations in multidisciplinary institutions," Journal of Informetrics, Elsevier, vol. 12(3), pages 736-756.
    2. Xie, Zheng & Ouyang, Zhenzheng & Li, Jianping, 2016. "A geometric graph model for coauthorship networks," Journal of Informetrics, Elsevier, vol. 10(1), pages 299-311.
    3. Zheng Xie & Zonglin Xie & Miao Li & Jianping Li & Dongyun Yi, 2017. "Modeling the coevolution between citations and coauthorship of scientific papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 483-507, July.

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