Generating process of emerging topics in the life sciences

Scientometrics volume 121, pages1549–1561(2019)Cite this article

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.

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Affiliations

  1. Faculty of Medicine, University of Tsukuba, Tennoh-dai, Tsukuba, 305-8575, Japan

    Ryosuke L. Ohniwa

  2. Center for Biotechnology, National Taiwan University, Taipei, 106, Taiwan

    Ryosuke L. Ohniwa

  3. Faculty of Humanities and Social Sciences, Hirosaki University, Hirosaki, 036-8560, Japan

    Aiko Hibino

Authors
  1. Ryosuke L. Ohniwa
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  2. Aiko Hibino
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Corresponding author

Correspondence to Ryosuke L. Ohniwa.

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The networks of the top 50 emerging keywords in 1971–1975. Only keywords that obtain links with other keywords are shown. The labels on the clusters represent the name of topics. The threshold for making edges was set as 10% of the number of keywords (selecting smaller sized nodes) linked by the edges. (TIFF 238 kb)

The networks of the top 50 emerging keywords in 1976–1980. See Supplemental Figure 1 legend for the conditions of links and labels. (TIFF 203 kb)

The networks of the top 50 emerging keywords in 1981–1985. See Supplemental Figure 1 legend for the conditions of links and labels. (TIFF 200 kb)

The networks of the top 50 emerging keywords in 1986–1990. See Supplemental Figure 1 legend for the conditions of links and labels. (TIFF 348 kb)

The networks of the top 50 emerging keywords in 1991–1995. See Supplemental Figure 1 legend for the conditions of links and labels. (TIFF 330 kb)

The networks of the top 50 emerging keywords in 1996–2000. See Supplemental Figure 1 legend for the conditions of links and labels. (TIFF 312 kb)

The networks of the top 50 emerging keywords in 2001–2005. See Supplemental Figure 1 legend for the conditions of links and labels. (TIFF 258 kb)

The networks of the top 50 emerging keywords in 2006–2010. See Supplemental Figure 1 legend for the conditions of links and labels. (TIFF 229 kb)

The networks of the top 50 emerging keywords in 2010–2015. See Supplemental Figure 1 legend for the conditions of links and labels. (TIFF 235 kb)

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Ohniwa, R.L., Hibino, A. Generating process of emerging topics in the life sciences. Scientometrics 121, 1549–1561 (2019). https://doi.org/10.1007/s11192-019-03248-z

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Keywords

  • Trends in life science
  • Emerging topics
  • MeSH terms
  • PubMed
  • Metrical index