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The emergent integrated network structure of scientific research

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  • Jordan D Dworkin
  • Russell T Shinohara
  • Danielle S Bassett

Abstract

Scientific research is often thought of as being conducted by individuals and small teams striving for disciplinary advances. Yet as a whole, this endeavor more closely resembles a complex and integrated system of people, papers, and ideas. Studies of co-authorship and citation networks have revealed important structural properties of researchers and articles, but currently the structure of scientific ideas themselves is not well understood. In this study, we posit that topic networks may be a useful framework for revealing the nature of conceptual relationships. Using this framework, we map the landscape of interconnected research topics covered in the multidisciplinary journal PNAS since 2000, constructing networks in which nodes represent topics of study and edges give the extent to which topics occur in the same papers. The network displays small-world architecture, characterized by regions of dense local connectivity with sparse connectivity between them. In this network, dense local connectivity additionally gives rise to distinct clusters of related topics. Yet notably, these clusters tend not to align with assigned article classifications, and instead contain topics from various disciplines. Using a temporal graph, we find that small-worldness has increased over time, suggesting growing efficiency and integration of ideas. Finally, we define two measures of interdisciplinarity, one of which is found to be positively associated with PNAS’s impact factor. Broadly, this work suggests that complex and dynamic patterns of knowledge emerge from scientific research, and that structures reflecting intellectual integration may be beneficial for obtaining scientific insight.

Suggested Citation

  • Jordan D Dworkin & Russell T Shinohara & Danielle S Bassett, 2019. "The emergent integrated network structure of scientific research," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-17, April.
  • Handle: RePEc:plo:pone00:0216146
    DOI: 10.1371/journal.pone.0216146
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    References listed on IDEAS

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    1. Daniel E. Acuna & Stefano Allesina & Konrad P. Kording, 2012. "Predicting scientific success," Nature, Nature, vol. 489(7415), pages 201-202, September.
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    1. Jingwei Zheng & Ke Zhang & Boya Han & Jiayi Hou, 2023. "Research Interdisciplinarity and Citation Impact: A Network Analysis of Social Networking Sites Research," SAGE Open, , vol. 13(3), pages 21582440231, August.

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