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Which are the best performing regions in information science in terms of highly cited papers? Some improvements of our previous mapping approaches

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  • Bornmann, Lutz
  • Leydesdorff, Loet

Abstract

Bornmann and Leydesdorff (2011) proposed methods based on Web of Science data to identify field-specific excellence in cities where highly cited papers were published more frequently than can be expected. Top performers in output are cities in which authors are located who publish a number of highly cited papers that is statistically significantly higher than can be expected for these cities. Using papers published between 1989 and 2009 in information science improvements to the methods of Bornmann and Leydesdorff (2011) are presented and an alternative mapping approach based on the Integrated Impact Indicator (I3) is introduced here. The I3 indicator was developed by Leydesdorff and Bornmann (2011b).

Suggested Citation

  • 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.
    • Handle: RePEc:eee:infome:v:6:y:2012:i:2:p:336-345
    DOI: 10.1016/j.joi.2011.11.002
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    References listed on IDEAS

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    1. Loet Leydesdorff & Olle Persson, 2010. "Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1622-1634, August.
    2. Richard Van Noorden, 2010. "Cities: Building the best cities for science," Nature, Nature, vol. 467(7318), pages 906-908, October.
    3. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    4. Bornmann, Lutz & Leydesdorff, Loet & Walch-Solimena, Christiane & Ettl, Christoph, 2011. "Mapping excellence in the geography of science: An approach based on Scopus data," Journal of Informetrics, Elsevier, vol. 5(4), pages 537-546.
    5. Adam Ozimek & Daniel Miles, 2011. "Stata utilities for geocoding and generating travel time and travel distance information," Stata Journal, StataCorp LP, vol. 11(1), pages 106-119, March.
    6. 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.
    7. Loet Leydesdorff & Lutz Bornmann, 2011. "How fractional counting of citations affects the impact factor: Normalization in terms of differences in citation potentials among fields of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 217-229, February.
    8. Bornmann, Lutz & Waltman, Ludo, 2011. "The detection of “hot regions” in the geography of science—A visualization approach by using density maps," Journal of Informetrics, Elsevier, vol. 5(4), pages 547-553.
    9. Loet Leydesdorff & Lutz Bornmann, 2011. "Integrated impact indicators compared with impact factors: An alternative research design with policy implications," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(11), pages 2133-2146, November.
    10. Opthof, Tobias & Leydesdorff, Loet, 2010. "Caveats for the journal and field normalizations in the CWTS (“Leiden”) evaluations of research performance," Journal of Informetrics, Elsevier, vol. 4(3), pages 423-430.
    11. Wolfgang Glänzel & Bart Thijs & András Schubert & Koenraad Debackere, 2009. "Subfield-specific normalized relative indicators and a new generation of relational charts: Methodological foundations illustrated on the assessment of institutional research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(1), pages 165-188, January.
    12. Loet Leydesdorff & Jung C. Shin, 2011. "How to evaluate universities in terms of their relative citation impacts: Fractional counting of citations and the normalization of differences among disciplines," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(6), pages 1146-1155, June.
    13. Lutz Bornmann & Rüdiger Mutz & Werner Marx & Hermann Schier & Hans‐Dieter Daniel, 2011. "A multilevel modelling approach to investigating the predictive validity of editorial decisions: do the editors of a high profile journal select manuscripts that are highly cited after publication?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(4), pages 857-879, October.
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    Cited by:

    1. Akella, Akhil Pandey & Alhoori, Hamed & Kondamudi, Pavan Ravikanth & Freeman, Cole & Zhou, Haiming, 2021. "Early indicators of scientific impact: Predicting citations with altmetrics," Journal of Informetrics, Elsevier, vol. 15(2).
    2. Copiello, Sergio, 2019. "Peer and neighborhood effects: Citation analysis using a spatial autoregressive model and pseudo-spatial data," Journal of Informetrics, Elsevier, vol. 13(1), pages 238-254.
    3. Mingyang Wang & Shi Li & Guangsheng Chen, 2017. "Detecting latent referential articles based on their vitality performance in the latest 2 years," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1557-1571, September.
    4. Giovanni Abramo & Tindaro Cicero & Ciriaco Andrea D’Angelo, 2013. "National peer-review research assessment exercises for the hard sciences can be a complete waste of money: the Italian case," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 311-324, April.
    5. 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.
    6. Alfonso Ibáñez & Pedro Larrañaga & Concha Bielza, 2013. "Cluster methods for assessing research performance: exploring Spanish computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 571-600, December.
    7. Wang, Mingyang & Yu, Guang & Xu, Jianzhong & He, Huixin & Yu, Daren & An, Shuang, 2012. "Development a case-based classifier for predicting highly cited papers," Journal of Informetrics, Elsevier, vol. 6(4), pages 586-599.
    8. Radu Silaghi-Dumitrescu & Augusta Sabau, 2014. "Scientometric analysis of relative performance in a key university in Romania," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 463-474, May.

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    More about this item

    Keywords

    Scientific excellence; Highly cited papers; I3; Geography of science; Spatial scientometrics; Google map;
    All these keywords.

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty

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