Generating process of emerging topics in the life sciences

Ryosuke L. Ohniwa () and Aiko Hibino
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Ryosuke L. Ohniwa: University of Tsukuba
Aiko Hibino: Hirosaki University

Scientometrics, 2019, vol. 121, issue 3, No 15, 1549-1561

Abstract: Abstract Clarifying the mechanism of how emerging topics in science and technology research fields are generated is useful for both researchers and agencies to identify potential emerging topics of the future. In the present study, we use bibliometric analyses targeting data of about 30 million published articles from 1970 to 2017 on PubMed, the largest article database in the life science field, to test our hypothesis that existing emerging topics contribute to the generation of new emerging topics in that field. We first collected emerging keywords from medical subject headings attached to each article using our previously reported methodology (Ohniwa et al. in Scientometrics 85(1):111–127, 2010, https://doi.org/10.1007/s11192-010-0252-2), and performed co-word analyses of each emerging keyword 1-year prior to it becoming an emerging keyword. About 75% of total emerging keywords, at 1-year prior to becoming identified as emerging, co-appeared with other emerging keywords in the same article. Furthermore, most of the keywords co-appeared again at the point when the target keyword was identified as emerging, which is consistent with our hypothesis regarding the mechanism that emerging topics generate emerging topics.

Keywords: Trends in life science; Emerging topics; MeSH terms; PubMed; Metrical index (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11192-019-03248-z

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