IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v107y2016i1d10.1007_s11192-016-1878-5.html
   My bibliography  Save this article

Evolution and structure of scientific co-publishing network in Korea between 1948–2011

Author

Listed:
  • Jinseok Kim

    (University of Illinois at Urbana-Champaign)

  • Liang Tao

    (University of Illinois at Urbana-Champaign)

  • Seok-Hyoung Lee

    (Korea Institute of Science and Technology Information)

  • Jana Diesner

    (University of Illinois at Urbana-Champaign)

Abstract

This study investigates the evolution and structure of a national-scale co-publishing network in Korea from 1948 to 2011. We analyzed more than 700,000 papers published by approximately 415,000 authors for temporal changes in productivity and network properties with a yearly resolution. The resulting statistical properties were compared to findings from previous studies of coauthorship networks at the national and discipline levels. Our results show that both the numbers of publications and authors in Korea have grown exponentially in a 64 year time frame. Korean scholars have become more productive and collaborative. They now form a small-world-ish network where most authors can connect with one other within an average of 5.33 degrees of separation. The increasingly skewed distribution and concentration of both productivity and the number of collaborators per author indicate that a relatively small group of individuals have accumulated a large number of opportunities for co-publishing. This implies a potential vulnerability for the network and its wider context: the graph would disintegrate into a multitude of smaller components, where the largest one would contain

Suggested Citation

  • Jinseok Kim & Liang Tao & Seok-Hyoung Lee & Jana Diesner, 2016. "Evolution and structure of scientific co-publishing network in Korea between 1948–2011," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(1), pages 27-41, April.
  • Handle: RePEc:spr:scient:v:107:y:2016:i:1:d:10.1007_s11192-016-1878-5
    DOI: 10.1007/s11192-016-1878-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-016-1878-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-016-1878-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andreas Strotmann & Dangzhi Zhao, 2012. "Author name disambiguation: What difference does it make in author-based citation analysis?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(9), pages 1820-1833, September.
    2. Kim, Jinseok & Diesner, Jana, 2015. "The effect of data pre-processing on understanding the evolution of collaboration networks," Journal of Informetrics, Elsevier, vol. 9(1), pages 226-236.
    3. Perc, Matjaž, 2010. "Growth and structure of Slovenia’s scientific collaboration network," Journal of Informetrics, Elsevier, vol. 4(4), pages 475-482.
    4. Cowan, Robin & Jonard, Nicolas, 2004. "Network structure and the diffusion of knowledge," Journal of Economic Dynamics and Control, Elsevier, vol. 28(8), pages 1557-1575, June.
    5. Garry Robins & Malcolm Alexander, 2004. "Small Worlds Among Interlocking Directors: Network Structure and Distance in Bipartite Graphs," Computational and Mathematical Organization Theory, Springer, vol. 10(1), pages 69-94, May.
    6. Fuyuki Yoshikane & Kyo Kageura, 2004. "Comparative analysis of coauthorship networks of different domains: The growth and change of networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(3), pages 435-446, August.
    7. Andreas Strotmann & Dangzhi Zhao, 2012. "Author name disambiguation: What difference does it make in author‐based citation analysis?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(9), pages 1820-1833, September.
    8. Barabási, A.L & Jeong, H & Néda, Z & Ravasz, E & Schubert, A & Vicsek, T, 2002. "Evolution of the social network of scientific collaborations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 311(3), pages 590-614.
    9. Borut Lužar & Zoran Levnajić & Janez Povh & Matjaž Perc, 2014. "Community Structure and the Evolution of Interdisciplinarity in Slovenia's Scientific Collaboration Network," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-5, April.
    10. Brent D Fegley & Vetle I Torvik, 2013. "Has Large-Scale Named-Entity Network Analysis Been Resting on a Flawed Assumption?," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-16, July.
    11. Han Woo Park & Loet Leydesdorff, 2008. "Korean journals in the Science Citation Index: What do they reveal about the intellectual structure of S&T in Korea?," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 439-462, June.
    12. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Murgia, Gianluca, 2013. "The collaboration behaviors of scientists in Italy: A field level analysis," Journal of Informetrics, Elsevier, vol. 7(2), pages 442-454.
    13. Massimo Franceschet, 2011. "Collaboration in computer science: A network science approach," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1992-2012, October.
    14. Helmut A. Abt, 2007. "The future of single-authored papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 73(3), pages 353-358, December.
    15. Waltman, Ludo, 2012. "An empirical analysis of the use of alphabetical authorship in scientific publishing," Journal of Informetrics, Elsevier, vol. 6(4), pages 700-711.
    16. Massimo Franceschet, 2011. "Collaboration in computer science: A network science approach," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(10), pages 1992-2012, October.
    17. Chen, Zifeng & Guan, Jiancheng, 2010. "The impact of small world on innovation: An empirical study of 16 countries," Journal of Informetrics, Elsevier, vol. 4(1), pages 97-106.
    18. András Schubert & Wolfgang Glänzel, 2006. "Cross-national preference in co-authorship, references and citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(2), pages 409-428, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sichao Tong & Per Ahlgren, 2017. "Evolution of three Nobel Prize themes and a Nobel snub theme in chemistry: a bibliometric study with focus on international collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 75-90, July.
    2. Andrej Kastrin & Jelena Klisara & Borut Lužar & Janez Povh, 2018. "Is science driven by principal investigators?," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1157-1182, November.
    3. Fan Jiang & Niancai Liu, 2018. "The hierarchical status of international academic awards in social sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 2091-2115, December.
    4. Jinseok Kim & Jana Diesner, 2019. "Formational bounds of link prediction in collaboration networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 687-706, May.
    5. Andrej Kastrin & Jelena Klisara & Borut Lužar & Janez Povh, 2017. "Analysis of Slovenian research community through bibliographic networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 791-813, February.
    6. Xuan Shi & Lingfei Cai & Junzhi Jia, 2018. "The Evolution of International Scientific Collaboration in Fuel Cells during 1998–2017: A Social Network Perspective," Sustainability, MDPI, vol. 10(12), pages 1-20, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kim, Jinseok & Diesner, Jana, 2015. "The effect of data pre-processing on understanding the evolution of collaboration networks," Journal of Informetrics, Elsevier, vol. 9(1), pages 226-236.
    2. Jinseok Kim, 2018. "Evaluating author name disambiguation for digital libraries: a case of DBLP," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1867-1886, September.
    3. Šubelj, Lovro & Fiala, Dalibor & Ciglarič, Tadej & Kronegger, Luka, 2019. "Convexity in scientific collaboration networks," Journal of Informetrics, Elsevier, vol. 13(1), pages 10-31.
    4. Peng Liu & Haoxiang Xia, 2015. "Structure and evolution of co-authorship network in an interdisciplinary research field," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 101-134, April.
    5. Jinseok Kim, 2019. "A fast and integrative algorithm for clustering performance evaluation in author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 661-681, August.
    6. Marian-Gabriel Hâncean & Matjaž Perc & Lazăr Vlăsceanu, 2014. "Fragmented Romanian Sociology: Growth and Structure of the Collaboration Network," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    7. Dangzhi Zhao & Andreas Strotmann, 2020. "Telescopic and panoramic views of library and information science research 2011–2018: a comparison of four weighting schemes for author co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 255-270, July.
    8. Vincenza Carchiolo & Marco Grassia & Michele Malgeri & Giuseppe Mangioni, 2022. "Co-Authorship Networks Analysis to Discover Collaboration Patterns among Italian Researchers," Future Internet, MDPI, vol. 14(6), pages 1-15, June.
    9. Xuan Zhen Liu & Hui Fang, 2014. "Scientific group leaders’ authorship preferences: an empirical investigation," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 909-925, February.
    10. Freeman, Richard B. & Huang, Wei, 2014. "Collaborating With People Like Me: Ethnic Co-authorship within the US," IZA Discussion Papers 8432, Institute of Labor Economics (IZA).
    11. Xie, Qing & Zhang, Xinyuan & Song, Min, 2021. "A network embedding-based scholar assessment indicator considering four facets: Research topic, author credit allocation, field-normalized journal impact, and published time," Journal of Informetrics, Elsevier, vol. 15(4).
    12. Richard B. Freeman & Wei Huang, 2015. "Collaborating with People Like Me: Ethnic Coauthorship within the United States," Journal of Labor Economics, University of Chicago Press, vol. 33(S1), pages 289-318.
    13. Javier Luis Cánovas Izquierdo & Valerio Cosentino & Jordi Cabot, 2016. "Analysis of co-authorship graphs of CORE-ranked software conferences," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1665-1693, December.
    14. Jinseok Kim & Jenna Kim & Jason Owen‐Smith, 2021. "Ethnicity‐based name partitioning for author name disambiguation using supervised machine learning," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(8), pages 979-994, August.
    15. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2019. "A gender analysis of top scientists’ collaboration behavior: evidence from Italy," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 405-418, August.
    16. Jinseok Kim & Jason Owen-Smith, 2021. "ORCID-linked labeled data for evaluating author name disambiguation at scale," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2057-2083, March.
    17. Rojko, Katarina & Lužar, Borut, 2022. "Scientific performance across research disciplines: Trends and differences in the case of Slovenia," Journal of Informetrics, Elsevier, vol. 16(2).
    18. Jean-Philippe Cointet & Camille Roth, 2007. "How Realistic Should Knowledge Diffusion Models Be?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1-5.
    19. Türker, İlker & Çavuşoğlu, Abdullah, 2016. "Detailing the co-authorship networks in degree coupling, edge weight and academic age perspective," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 386-392.
    20. Noémi Gaskó & Rodica Ioana Lung & Mihai Alexandru Suciu, 2016. "A new network model for the study of scientific collaborations: Romanian computer science and mathematics co-authorship networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 613-632, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:107:y:2016:i:1:d:10.1007_s11192-016-1878-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.