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Journal portfolio analysis for countries, cities, and organizations: Maps and comparisons

Author

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  • Loet Leydesdorff
  • Gaston Heimeriks
  • Daniele Rotolo

Abstract

Using Web-of-Science data, portfolio analysis in terms of journal coverage can be projected on a base map for units of analysis such as countries, cities, universities, and firms. The units of analysis under study can be compared statistically across the 10,000+ journals. The interdisciplinarity of the portfolios is measured using Rao-Stirling diversity or the 2D3 measure proposed by Zhang et al. (2015). At the country level we find regional differentiation (e.g., Latin-American or Asian countries), but also a major divide between advanced and less-developed countries. Israel and Israeli cities outperform other nations and cities in terms of diversity. Universities appear to be specifically related to firms when a number of these units are exploratively compared. The instrument is relatively simple and straightforward, and one can generalize the application to any document set retrieved from the Web-of-Science (WoS). Further instruction is provided online at http://www.leydesdorff.net/portfolio.
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Suggested Citation

  • Loet Leydesdorff & Gaston Heimeriks & Daniele Rotolo, 2016. "Journal portfolio analysis for countries, cities, and organizations: Maps and comparisons," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(3), pages 741-748, March.
    • Handle: RePEc:bla:jinfst:v:67:y:2016:i:3:p:741-748
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    File URL: http://hdl.handle.net/10.1002/asi.23551
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    Cited by:

    1. Roman Jurowetzki, 2015. "Unpacking Big Systems - Natural Language Processing meets Network Analysis. A Study of Smart Grid Development in Denmark," SPRU Working Paper Series 2015-15, SPRU - Science Policy Research Unit, University of Sussex Business School.
    2. Javier López González & Valentina Meliciani & Maria Savona, 2019. "When Linder meets Hirschman: inter-industry linkages and global value chains in business services," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(6), pages 1555-1586.
    3. Loet Leydesdorff & Dieter Franz Kogler & Bowen Yan, 2017. "Mapping patent classifications: portfolio and statistical analysis, and the comparison of strengths and weaknesses," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1573-1591, September.
    4. Janaina Pamplona da Costa, 2015. "Network (Mis)Alignment, Technology Policy and Innovation: The Tale of Two Brazilian Cities," SPRU Working Paper Series 2015-14, SPRU - Science Policy Research Unit, University of Sussex Business School.
    5. Phil Johnstone & Andy Stirling, 2015. "Comparing Nuclear Power Trajectories inGermany And the UK: From ‘Regimes’ to ‘Democracies’ in Sociotechnical Transitions and Discontinuities," SPRU Working Paper Series 2015-18, SPRU - Science Policy Research Unit, University of Sussex Business School.
    6. Jungjoon Kim & Sangpil Lee & We Shim & Jongseok Kang, 2016. "A Mapping of Marine Biodiversity Research Trends and Collaboration in the East Asia Region from 1996–2015," Sustainability, MDPI, vol. 8(10), pages 1-17, October.
    7. Muhammad Omar & Arif Mehmood & Gyu Sang Choi & Han Woo Park, 2017. "Global mapping of artificial intelligence in Google and Google Scholar," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1269-1305, December.
    8. Leydesdorff, Loet & Bornmann, Lutz & Zhou, Ping, 2016. "Construction of a pragmatic base line for journal classifications and maps based on aggregated journal-journal citation relations," Journal of Informetrics, Elsevier, vol. 10(4), pages 902-918.
    9. A. I. M. Jakaria Rahman & Raf Guns & Loet Leydesdorff & Tim C. E. Engels, 2016. "Measuring the match between evaluators and evaluees: cognitive distances between panel members and research groups at the journal level," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1639-1663, December.

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