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Complex networks reveal emergent interdisciplinary knowledge in Wikipedia

Author

Listed:
  • Gustavo A. Schwartz

    (Centro de Física de Materiales (CSIC-UPV/EHU)—Materials Physics Center (MPC)
    Donostia International Physics Center)

Abstract

In the last 2 decades, a great amount of work has been done on data mining and knowledge discovery using complex networks. These works have provided insightful information about the structure and evolution of scientific activity, as well as important biomedical discoveries. However, interdisciplinary knowledge discovery, including disciplines other than science, is more complicated to implement because most of the available knowledge is not indexed. Here, a new method is presented for mining Wikipedia to unveil implicit interdisciplinary knowledge to map and understand how different disciplines (art, science, literature) are related to and interact with each other. Furthermore, the formalism of complex networks allows us to characterise both individual and collective behaviour of the different elements (people, ideas, works) within each discipline and among them. The results obtained agree with well-established interdisciplinary knowledge and show the ability of this method to boost quantitative studies. Note that relevant elements in different disciplines that rarely directly refer to each other may nonetheless have many implicit connections that impart them and their relationship with new meaning. Owing to the large number of available works and to the absence of cross-references among different disciplines, tracking these connections can be challenging. This approach aims to bridge this gap between the large amount of reported knowledge and the limited human capacity to find subtle connections and make sense of them.

Suggested Citation

  • Gustavo A. Schwartz, 2021. "Complex networks reveal emergent interdisciplinary knowledge in Wikipedia," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-6, December.
    • Handle: RePEc:pal:palcom:v:8:y:2021:i:1:d:10.1057_s41599-021-00801-1
    DOI: 10.1057/s41599-021-00801-1
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    References listed on IDEAS

    as
    1. 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.
    2. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
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    Cited by:

    1. Xiaobiao Lin & Shidai Wu & Bowei Wu & Jiawei Wang, 2024. "Quantifying the diffusion history of Yangmingism," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    2. Li, Jing & Yu, Qian, 2024. "Scientists’ disciplinary characteristics and collaboration behaviour under the convergence paradigm: A multilevel network perspective," Journal of Informetrics, Elsevier, vol. 18(1).
    3. Shenzhen Tian & Jialin Jiang & Hang Li & Xueming Li & Jun Yang & Chuanglin Fang, 2023. "Flow space reveals the urban network structure and development mode of cities in Liaoning, China," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.

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