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Assessing an author's influence using time series historiographic mapping: The oeuvre of conrad hal waddington (1905–1975)

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  • Katherine W. McCain

Abstract

A modified approach to algorithmic historiography is used to investigate the changing influence of the work of Conrad Hal Waddington over the period 1945–2004. Overall, Waddington's publications were cited by almost 5,500 source items in the Web of Science (Thomson Scientific, formerly Thomson ISI, Philadelphia, PA). Rather than simply analyzing the data set as a whole, older works by Waddington are incorporated into a series of historiographic maps (networks of highly cited documents), which show long‐term and short‐term research themes grounded in Waddington's work. Analysis by 10–20‐year periods and the use of social network analysis soft‐ ware reveals structures—thematic networks and subnetworks—that are hidden in a mapping of the entire 60‐year period. Two major Waddington‐related themes emerge—canalization/genetic assimilation and embryonic induction. The first persists over the 60 years studied while active, visible research in the second appears to have declined markedly between 1965 and 1984, only to reappear in conjunction with the emergence of a new research field—Evolutionary Developmental Biology.

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  • Katherine W. McCain, 2008. "Assessing an author's influence using time series historiographic mapping: The oeuvre of conrad hal waddington (1905–1975)," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(4), pages 510-525, February.
    • Handle: RePEc:bla:jamist:v:59:y:2008:i:4:p:510-525
    DOI: 10.1002/asi.20705
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    Cited by:

    1. Huang, Lu & Chen, Xiang & Ni, Xingxing & Liu, Jiarun & Cao, Xiaoli & Wang, Changtian, 2021. "Tracking the dynamics of co-word networks for emerging topic identification," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    2. Lu Huang & Xiang Chen & Yi Zhang & Changtian Wang & Xiaoli Cao & Jiarun Liu, 2022. "Identification of topic evolution: network analytics with piecewise linear representation and word embedding," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5353-5383, September.
    3. McCain, Katherine W., 2010. "Core journal literatures and persistent research themes in an emerging interdisciplinary field: Exploring the literature of evolutionary developmental biology," Journal of Informetrics, Elsevier, vol. 4(2), pages 157-165.
    4. Xiaoguang Wang & Qikai Cheng & Wei Lu, 2014. "Analyzing evolution of research topics with NEViewer: a new method based on dynamic co-word networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1253-1271, November.
    5. Budler, Marko & Župič, Ivan & Trkman, Peter, 2021. "The development of business model research: A bibliometric review," Journal of Business Research, Elsevier, vol. 135(C), pages 480-495.

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