IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v102y2015i1d10.1007_s11192-014-1419-z.html
   My bibliography  Save this article

Network analysis of Zentralblatt MATH data

Author

Listed:
  • Monika Cerinšek

    (Hruška d.o.o.)

  • Vladimir Batagelj

    (University of Ljubljana)

Abstract

We analyze the data about works (papers, books) from the time period 1990–2010 that are collected in Zentralblatt MATH database. The data were converted into four 2-mode networks (works $$\times $$ × authors, works $$\times $$ × journals, works $$\times $$ × keywords and works $$\times $$ × mathematical subject classifications) and into a partition of works by publication year. The networks were analyzed using Pajek—a program for analysis and visualization of large networks. We explore the distributions of some properties of works and the collaborations among mathematicians. We also take a closer look at the characteristics of the field of graph theory as were realized with the publications.

Suggested Citation

  • Monika Cerinšek & Vladimir Batagelj, 2015. "Network analysis of Zentralblatt MATH data," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 977-1001, January.
    • Handle: RePEc:spr:scient:v:102:y:2015:i:1:d:10.1007_s11192-014-1419-z
    DOI: 10.1007/s11192-014-1419-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-014-1419-z
    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/s11192-014-1419-z?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. Vladimir Batagelj & Matjaž Zaveršnik, 2011. "Fast algorithms for determining (generalized) core groups in social networks," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(2), pages 129-145, July.
    2. Vladimir Batagelj & Monika Cerinšek, 2013. "On bibliographic networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 845-864, September.
    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. Batagelj, Vladimir & Maltseva, Daria, 2020. "Temporal bibliographic networks," Journal of Informetrics, Elsevier, vol. 14(1).
    2. Perianes-Rodriguez, Antonio & Waltman, Ludo & van Eck, Nees Jan, 2016. "Constructing bibliometric networks: A comparison between full and fractional counting," Journal of Informetrics, Elsevier, vol. 10(4), pages 1178-1195.
    3. Gangan Prathap & Somenath Mukherjee, 2020. "Letter to the Editor: Comments on the paper of Batagelj—on fractional approach to analysis of linked networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2717-2722, September.

    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. Ion Georgiou & Joaquim Heck & Andrej Mrvar, 2019. "The Analysis of Interconnected Decision Areas: A Computational Approach to Finding All Feasible Solutions," Group Decision and Negotiation, Springer, vol. 28(3), pages 543-563, June.
    2. Santana, Monica & Cobo, Manuel J., 2020. "What is the future of work? A science mapping analysis," European Management Journal, Elsevier, vol. 38(6), pages 846-862.
    3. Gangan Prathap & Somenath Mukherjee, 2020. "Letter to the Editor: Comments on the paper of Batagelj—on fractional approach to analysis of linked networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2717-2722, September.
    4. 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.
    5. Saxena, Rakhi & Kaur, Sharanjit & Bhatnagar, Vasudha, 2019. "Identifying similar networks using structural hierarchy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    6. A. Velez-Estevez & P. García-Sánchez & J. A. Moral-Munoz & M. J. Cobo, 2022. "Why do papers from international collaborations get more citations? A bibliometric analysis of Library and Information Science papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7517-7555, December.
    7. Miltos Ladikas & Julia Hahn & Lei Huang, 2022. "Assessing the Impact of Technology Assessment, Responsible Research and Innovation and Sustainability Research: Towards a Common Methodological Approach," Sustainability, MDPI, vol. 14(4), pages 1-16, February.
    8. Daria Maltseva & Vladimir Batagelj, 2020. "Towards a systematic description of the field using keywords analysis: main topics in social networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 357-382, April.
    9. Monica Santana & Alvaro Lopez‐Cabrales, 2019. "Sustainable development and human resource management: A science mapping approach," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 26(6), pages 1171-1183, November.
    10. Susan George & Hiran H. Lathabai & Thara Prabhakaran & Manoj Changat, 2020. "A framework towards bias-free contextual productivity assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 127-157, January.
    11. Vincenzo Giuseppe Genova & Giuseppe Giordano & Giancarlo Ragozini & Maria Prosperina Vitale, 2024. "An analytic strategy for data processing of multimode networks," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(3), pages 745-767, September.
    12. Clemente-Gallardo, J. & Ferrer, A. & Íñiguez, D. & Rivero, A. & Ruiz, G. & Tarancón, A., 2019. "Do researchers collaborate in a similar way to publish and to develop projects?," Journal of Informetrics, Elsevier, vol. 13(1), pages 64-77.
    13. Aristotelis Mavidis & Dimitris Folinas & Dimitrios Skiadas & Alexandros Xanthopoulos, 2024. "Emerging Technologies Revolutionising Public Procurement: Insights from Comprehensive Bibliometric Analysis," Administrative Sciences, MDPI, vol. 14(2), pages 1-29, January.
    14. Vladimir Batagelj & Monika Cerinšek, 2013. "On bibliographic networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 845-864, September.
    15. Vladimir Batagelj & Anuška Ferligoj & Flaminio Squazzoni, 2017. "The emergence of a field: a network analysis of research on peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 503-532, October.
    16. Vladimir Batagelj, 2020. "On fractional approach to analysis of linked networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 621-633, May.
    17. Daria Maltseva & Vladimir Batagelj, 2020. "iMetrics: the development of the discipline with many names," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 313-359, October.
    18. Marco Mancastroppa & Iacopo Iacopini & Giovanni Petri & Alain Barrat, 2023. "Hyper-cores promote localization and efficient seeding in higher-order processes," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    19. Maria Prosperina Vitale & Giuseppe Giordano & Giancarlo Ragozini, 2022. "Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 269-278, June.
    20. Vladimir Batagelj, 2024. "On weighted two-mode network projections," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3565-3571, June.

    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:102:y:2015:i:1:d:10.1007_s11192-014-1419-z. 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.