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Which cities produce more excellent papers than can be expected? A new mapping approach, using Google Maps, based on statistical significance testing

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  • Lutz Bornmann
  • Loet Leydesdorff

Abstract

The methods presented in this paper allow for a statistical analysis revealing centers of excellence around the world using programs that are freely available. Based on Web of Science data (a fee‐based database), field‐specific excellence can be identified in cities where highly cited papers were published more frequently than can be expected. Compared to the mapping approaches published hitherto, our approach is more analytically oriented by allowing the assessment of an observed number of excellent papers for a city against the expected number. Top performers in output are cities in which authors are located who publish a statistically significant higher number of highly cited papers than can be expected for these cities. As sample data for physics, chemistry, and psychology show, these cities do not necessarily have a high output of highly cited papers.

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  • Lutz Bornmann & Loet Leydesdorff, 2011. "Which cities produce more excellent papers than can be expected? A new mapping approach, using Google Maps, based on statistical significance testing," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1954-1962, October.
  • Handle: RePEc:bla:jamist:v:62:y:2011:i:10:p:1954-1962
    DOI: 10.1002/asi.21611
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    12. Ismael Rafols & Loet Leydesdorff, 2009. "Content‐based and algorithmic classifications of journals: Perspectives on the dynamics of scientific communication and indexer effects," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(9), pages 1823-1835, September.
    13. Veljko Jeremic & Milica Bulajic & Milan Martic & Zoran Radojicic, 2011. "A fresh approach to evaluating the academic ranking of world universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 587-596, June.
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    Cited by:

    1. Guangyao Zhang & Yuqi Wang & Weixi Xie & Han Du & Chunlin Jiang & Xianwen Wang, 2021. "The open access usage advantage: a temporal and spatial analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6187-6199, July.
    2. Loet Leydesdorff, 2012. "Alternatives to the journal impact factor: I3 and the top-10% (or top-25%?) of the most-highly cited papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(2), pages 355-365, August.
    3. Stefan Hennemann, 2012. "Evaluating the performance of geographical locations within scientific networks using an aggregation—randomization—re-sampling approach (ARR)," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2393-2404, December.
    4. Juan A Crespo & Ignacio Ortuño-Ortín & Javier Ruiz-Castillo, 2012. "The Citation Merit of Scientific Publications," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-9, November.
    5. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2014. "Assessing national strengths and weaknesses in research fields," Journal of Informetrics, Elsevier, vol. 8(3), pages 766-775.
    6. Loet Leydesdorff, 2013. "An evaluation of impacts in “Nanoscience & nanotechnology”: steps towards standards for citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 35-55, January.
    7. F. Cugnata & G. Perucca & S. Salini, 2017. "Bayesian networks and the assessment of universities' value added," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(10), pages 1785-1806, July.
    8. Milica Jovanovic & Veljko Jeremic & Gordana Savic & Milica Bulajic & Milan Martic, 2012. "How does the normalization of data affect the ARWU ranking?," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(2), pages 319-327, November.
    9. Loet Leydesdorff & Duncan Kushnir & Ismael Rafols, 2014. "Interactive overlay maps for US patent (USPTO) data based on International Patent Classification (IPC)," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1583-1599, March.
    10. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2015. "Ranking research institutions by the number of highly-cited articles per scientist," Journal of Informetrics, Elsevier, vol. 9(4), pages 915-923.
    11. Csomós, György, 2018. "Reprint of “A spatial scientometric analysis of the publication output of cities worldwide”," Journal of Informetrics, Elsevier, vol. 12(2), pages 547-566.
    12. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    13. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2020. "A novel methodology to assess the scientific standing of nations at field level," Journal of Informetrics, Elsevier, vol. 14(1).
    14. Loet Leydesdorff & Lutz Bornmann, 2012. "Mapping (USPTO) patent data using overlays to Google Maps," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1442-1458, July.
    15. Bornmann, Lutz & Ozimek, Adam, 2012. "Stata commands for importing bibliometric data and processing author address information," Journal of Informetrics, Elsevier, vol. 6(4), pages 505-512.
    16. Loet Leydesdorff & Daniele Rotolo & Ismael Rafols, 2012. "Bibliometric perspectives on medical innovation using the medical subject Headings of PubMed," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2239-2253, November.
    17. Bornmann, Lutz & Stefaner, Moritz & de Moya Anegón, Felix & Mutz, Rüdiger, 2014. "What is the effect of country-specific characteristics on the research performance of scientific institutions? Using multi-level statistical models to rank and map universities and research-focused in," Journal of Informetrics, Elsevier, vol. 8(3), pages 581-593.
    18. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2015. "A methodology to compute the territorial productivity of scientists: The case of Italy," Journal of Informetrics, Elsevier, vol. 9(4), pages 675-685.
    19. Bornmann, Lutz & Leydesdorff, Loet, 2012. "Which are the best performing regions in information science in terms of highly cited papers? Some improvements of our previous mapping approaches," Journal of Informetrics, Elsevier, vol. 6(2), pages 336-345.
    20. Giovanni Abramo & Francesca Apponi & Ciriaco Andrea D’Angelo, 2024. "Do research universities specialize in disciplines where they hold a competitive advantage?," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5453-5468, September.
    21. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2014. "Are the authors of highly cited articles also the most productive ones?," Journal of Informetrics, Elsevier, vol. 8(1), pages 89-97.
    22. Bornmann, Lutz & Leydesdorff, Loet & Mutz, Rüdiger, 2013. "The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits," Journal of Informetrics, Elsevier, vol. 7(1), pages 158-165.
    23. Loet Leydesdorff & Floortje Alkemade & Gaston Heimeriks & Rinke Hoekstra, 2015. "Patents as instruments for exploring innovation dynamics: geographic and technological perspectives on “photovoltaic cells”," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 629-651, January.
    24. Daniele Rotolo & Ismael Rafols & Michael Hopkins & Loet Leydesdorff, 2014. "Scientometric Mapping as a Strategic Intelligence Tool for the Governance of Emerging Technologies," SPRU Working Paper Series 2014-10, SPRU - Science Policy Research Unit, University of Sussex Business School.
    25. Michel Grossetti & Denis Eckert & Yves Gingras & Laurent Jégou & Vincent Larivière & Béatrice Milard, 2014. "Cities and the geographical deconcentration of scientific activity: A multilevel analysis of publications (1987–2007)," Urban Studies, Urban Studies Journal Limited, vol. 51(10), pages 2219-2234, August.

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