Dynamics of topic formation and quantitative analysis of hot trends in physical science

A. V. Chumachenko (), B. G. Kreminskyi, Iu. L. Mosenkis and A. I. Yakimenko
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A. V. Chumachenko: Taras Shevchenko National University of Kyiv
B. G. Kreminskyi: State Scientific Institution “Institute of Education Content Modernization”
Iu. L. Mosenkis: Taras Shevchenko National University of Kyiv
A. I. Yakimenko: Taras Shevchenko National University of Kyiv

Scientometrics, 2020, vol. 125, issue 1, No 31, 739-753

Abstract: Abstract Successful research in the face of increasing complexity of modern scientific knowledge together with diversity and depth of the studied problems requires an understanding of the structure and evolution of trends in science. Available digital records open wide possibilities for statistical analysis of scientific publications and related metadata for topic modeling and evolution, knowledge mapping, citation indexing, etc. We investigate dynamical properties of the physical topics using analysis of temporal evolution of proximity measure for word pairs related to the mutual information. We use full-text conceptualization of content of scientific documents provided by the ScienceWISE platform for topic mapping, trend analysis and detection of hot topics together with relevant papers retrieval. We found that time evolution of relative mutual information distance reveals a hidden topic structure and could be used for quantitative analysis of current trends in scientific research.

Keywords: Dynamical complex networks; Topic detection; Mutual information dynamics; Topic structure; Concept mapping; 94A17; 05C62; 37E25 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11192-020-03610-6

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