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The geography of scientific citations

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  • Wuestman, Mignon L.
  • Hoekman, Jarno
  • Frenken, Koen

Abstract

Science’s main norms prescribe scientists to use citations as acknowledgements of cognitive content irrespective of geographical location. Previous studies, however, suggested that there is a considerable geographical bias in scientific citations. We argue that this geographical bias does not, in itself, falsify the notion that citations reflect acknowledgement of cognitive content, because cognitively related knowledge may be geographically concentrated as well. We analyse the role of organizational, regional and national co-location on citation likelihood for 5.5 million article pairs, and find that the geographical bias in citations is weak once cognitive relatedness is accounted for. Furthermore, we find that the effect of co-location on citation likelihood is strongest at the organizational level, weaker at the regional level, and weakest at the national level. In addition, we show that geographical co-location particularly increases the citation likelihood between two papers when knowledge relatedness between articles is low, suggesting that interdisciplinary research benefits most from co-location. Finally, we find that, when knowledge relatedness is high, the effect of geographical co-location on citation likelihood is non-existent. We discuss the implications regarding policies aimed to discourage strategic citations and to foster interdisciplinary research.

Suggested Citation

  • Wuestman, Mignon L. & Hoekman, Jarno & Frenken, Koen, 2019. "The geography of scientific citations," Research Policy, Elsevier, vol. 48(7), pages 1771-1780.
  • Handle: RePEc:eee:respol:v:48:y:2019:i:7:p:1771-1780
    DOI: 10.1016/j.respol.2019.04.004
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    2. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Di Costa, Flavia, 2020. "Knowledge spillovers: Does the geographic proximity effect decay over time? A discipline-level analysis, accounting for cognitive proximity, with and without self-citations," Journal of Informetrics, Elsevier, vol. 14(4).
    3. Abdelghani Maddi & Lesya Baudoin, 2022. "The quality of the web of science data: a longitudinal study on the completeness of authors-addresses links," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6279-6292, November.
    4. Wei Ming & Zhenyue Zhao, 2022. "Rethinking the open access citation advantage: Evidence from the “reverse‐flipping” journals," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(11), pages 1608-1620, November.
    5. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Di Costa, Flavia, 2021. "On the relation between the degree of internationalization of cited and citing publications: A field level analysis, including and excluding self-citations," Journal of Informetrics, Elsevier, vol. 15(1).
    6. Andrea Fronzetti Colladon & Ciriaco Andrea D’Angelo & Peter A. Gloor, 2020. "Predicting the future success of scientific publications through social network and semantic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 357-377, July.
    7. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Di Costa, Flavia, 2020. "The role of geographical proximity in knowledge diffusion, measured by citations to scientific literature," Journal of Informetrics, Elsevier, vol. 14(1).
    8. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2020. "Does the geographic proximity effect on knowledge spillovers vary across research fields?," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1021-1036, May.
    9. Yan, Xiaoqin & Bao, Honglin & Leppard, Tom & Davis, Andrew, 2024. "Cultural Ties in Knowledge Production," SocArXiv qvyj8, Center for Open Science.
    10. Marginson, Simon, 2021. "National modernisation and global science in China," International Journal of Educational Development, Elsevier, vol. 84(C).

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