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Institutional interactions: Exploring social, cognitive, and geographic relationships between institutions as demonstrated through citation networks

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  • Erjia Yan
  • Cassidy R. Sugimoto

Abstract

The objective of this research is to examine the interaction of institutions, based on their citation and collaboration networks. The domain of library and information science is examined, using data from 1965–2010. A linear model is formulated to explore the factors that are associated with institutional citation behaviors, using the number of citations as the dependent variable, and the number of collaborations, physical distance, and topical distance as independent variables. It is found that institutional citation behaviors are associated with social, topical, and geographical factors. Dynamically, the number of citations is becoming more associated with collaboration intensity and less dependent on the country boundary and/or physical distance. This research is informative for scientometricians and policy makers.

Suggested Citation

  • Erjia Yan & Cassidy R. Sugimoto, 2011. "Institutional interactions: Exploring social, cognitive, and geographic relationships between institutions as demonstrated through citation networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(8), pages 1498-1514, August.
    • Handle: RePEc:bla:jamist:v:62:y:2011:i:8:p:1498-1514
    DOI: 10.1002/asi.21556
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    Citations

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    Cited by:

    1. 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.
    2. Pu Han & Jin Shi & Xiaoyan Li & Dongbo Wang & Si Shen & Xinning Su, 2014. "International collaboration in LIS: global trends and networks at the country and institution level," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 53-72, January.
    3. Per Ahlgren & Olle Persson & Robert Tijssen, 2013. "Geographical distance in bibliometric relations within epistemic communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 771-784, May.
    4. Guo Chen & Lu Xiao & Chang-ping Hu & Xue-qin Zhao, 2015. "Identifying the research focus of Library and Information Science institutions in China with institution-specific keywords," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 707-724, May.
    5. Wang, Jue & Zhang, Liwei, 2018. "Proximal advantage in knowledge diffusion: The time dimension," Journal of Informetrics, Elsevier, vol. 12(3), pages 858-867.
    6. Pan, Xuelian & Yan, Erjia & Wang, Qianqian & Hua, Weina, 2015. "Assessing the impact of software on science: A bootstrapped learning of software entities in full-text papers," Journal of Informetrics, Elsevier, vol. 9(4), pages 860-871.
    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. Yuanyuan Liu & Qiang Wu & Shijie Wu & Yong Gao, 2021. "Weighted citation based on ranking-related contribution: a new index for evaluating article impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8653-8672, October.
    9. Zhao, Star X. & Ye, Fred Y., 2012. "Exploring the directed h-degree in directed weighted networks," Journal of Informetrics, Elsevier, vol. 6(4), pages 619-630.
    10. Reut Snir & Gilad Ravid, 2016. "Global nanotechnology regulatory governance from a network analysis perspective," Regulation & Governance, John Wiley & Sons, vol. 10(4), pages 314-334, December.
    11. Shan Jiang & Hsinchun Chen, 2019. "Examining patterns of scientific knowledge diffusion based on knowledge cyber infrastructure: a multi-dimensional network approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1599-1617, December.
    12. Lili Yuan & Yanni Hao & Minglu Li & Chunbing Bao & Jianping Li & Dengsheng Wu, 2018. "Who are the international research collaboration partners for China? A novel data perspective based on NSFC grants," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 401-422, July.
    13. Yan, Erjia & Guns, Raf, 2014. "Predicting and recommending collaborations: An author-, institution-, and country-level analysis," Journal of Informetrics, Elsevier, vol. 8(2), pages 295-309.
    14. Erjia Yan, 2014. "Topic-based Pagerank: toward a topic-level scientific evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 407-437, August.
    15. Feiheng Luo & Aixin Sun & Mojisola Erdt & Aravind Sesagiri Raamkumar & Yin-Leng Theng, 2018. "Exploring prestigious citations sourced from top universities in bibliometrics and altmetrics: a case study in the computer science discipline," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 1-17, January.
    16. 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.
    17. Yongjun Zhu & Erjia Yan, 2015. "Dynamic subfield analysis of disciplines: an examination of the trading impact and knowledge diffusion patterns of computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 335-359, July.
    18. He, Bing & Ding, Ying & Yan, Erjia, 2012. "Mining patterns of author orders in scientific publications," Journal of Informetrics, Elsevier, vol. 6(3), pages 359-367.
    19. Saeed-Ul Hassan & Iqra Safder & Anam Akram & Faisal Kamiran, 2018. "A novel machine-learning approach to measuring scientific knowledge flows using citation context analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 973-996, August.
    20. Yan, Erjia & Ding, Ying & Cronin, Blaise & Leydesdorff, Loet, 2013. "A bird's-eye view of scientific trading: Dependency relations among fields of science," Journal of Informetrics, Elsevier, vol. 7(2), pages 249-264.
    21. Federica Bologna & Angelo Iorio & Silvio Peroni & Francesco Poggi, 2023. "Do open citations give insights on the qualitative peer-review evaluation in research assessments? An analysis of the Italian National Scientific Qualification," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 19-53, January.
    22. Yan, Erjia, 2014. "Research dynamics: Measuring the continuity and popularity of research topics," Journal of Informetrics, Elsevier, vol. 8(1), pages 98-110.

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