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How to analyze publication time trends by correspondence factor analysis: Analysis of publications by 48 countries in 18 disciplines over 12 years

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  • Jean‐Christophe Doré
  • Tiiu Ojasoo

Abstract

This study is a follow‐up to a published Correspondence Factorial Analysis (CFA) of a dataset of over 6 million bibliometric entries (Doré et al. JASIS, 47(8), 588– 602,1996), which compared the publication output patterns of 48 countries in 18 disciplines over a 12‐year period (1981–1992). It analyzes by methods suitable for investigating short time series how these output patterns evolved over the 12‐year span. Three types of approach are described: (1) the chi2 distances of the publication output patterns from the center of gravity of the multidimensional system—which represents an average world pattern—were calculated for each country and for each year. We noted whether the patterns moved toward or away from the center with time; (2) individual annual output patterns were introduced as supplementary variables into an existing global overview covering the whole time‐span [CFA map of (countries × disciplines)]. We observed how these patterns moved about within the map year by year; (3) the matrix (disciplines × time) was analyzed by CFA to derive time trends for each country. CFA revealed the “inner clocks” governing publication trends. The time scale that best fitted the data was not a linear but an elastic scale. Although different countries laid emphasis on publication in different disciplines, the overall tendency was toward greater uniformity in publication patterns with time.

Suggested Citation

  • Jean‐Christophe Doré & Tiiu Ojasoo, 2001. "How to analyze publication time trends by correspondence factor analysis: Analysis of publications by 48 countries in 18 disciplines over 12 years," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 52(9), pages 763-769.
  • Handle: RePEc:bla:jamist:v:52:y:2001:i:9:p:763-769
    DOI: 10.1002/asi.1130
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    Cited by:

    1. Richard Klavans & Kevin W Boyack, 2017. "The Research Focus of Nations: Economic vs. Altruistic Motivations," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-27, January.
    2. Ebadi, Ashkan & Tremblay, Stéphane & Goutte, Cyril & Schiffauerova, Andrea, 2020. "Application of machine learning techniques to assess the trends and alignment of the funded research output," Journal of Informetrics, Elsevier, vol. 14(2).
    3. Carlos Suárez-Balseiro & Elias Sanz-Casado & Laurie Ortiz-Rivera, 2006. "Patterns of international scientific co-operation in Puerto Rico," Scientometrics, Springer;Akadémiai Kiadó, vol. 67(3), pages 335-350, June.
    4. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    5. Rousseau, Ronald & Hu, Xiaojun, 2013. "Two time series, their meaning and some applications," Journal of Informetrics, Elsevier, vol. 7(3), pages 603-610.

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