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On bibliographic networks

Author

Listed:
  • Vladimir Batagelj

    (University of Ljubljana)

  • Monika Cerinšek

    (Hruška d.o.o.)

Abstract

In the paper we show that the bibliographic data can be transformed into a collection of compatible networks. Using network multiplication different interesting derived networks can be obtained. In defining them an appropriate normalization should be considered. The proposed approach can be applied also to other collections of compatible networks. The networks obtained from the bibliographic data bases can be large (hundreds of thousands of vertices). Fortunately they are sparse and can be still processed relatively fast. We answer the question when the multiplication of sparse networks preserves sparseness. The proposed approaches are illustrated with analyses of collection of networks on the topic "social network" obtained from the Web of Science. The works with large number of co-authors add large complete subgraphs to standard collaboration network thus bluring the collaboration structure. We show that using an appropriate normalization their effect can be neutralized. Among other, we propose a measure of collaborativness of authors with respect to a given bibliography and show how to compute the network of citations between authors and identify citation communities.

Suggested Citation

  • Vladimir Batagelj & Monika Cerinšek, 2013. "On bibliographic networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 845-864, September.
  • Handle: RePEc:spr:scient:v:96:y:2013:i:3:d:10.1007_s11192-012-0940-1
    DOI: 10.1007/s11192-012-0940-1
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    References listed on IDEAS

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    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. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    3. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
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    Citations

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    Cited by:

    1. Daria Maltseva & Vladimir Batagelj, 2021. "Journals publishing social network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3593-3620, April.
    2. Batagelj, Vladimir & Maltseva, Daria, 2020. "Temporal bibliographic networks," Journal of Informetrics, Elsevier, vol. 14(1).
    3. 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.
    4. 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.
    5. 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.
    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. Thara Prabhakaran & Hiran H. Lathabai & Susan George, 2019. "Competing, complementary and co-existing paradigms in techno-scientific literature: A case study of Nanotechnology for engineering," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 941-977, March.
    8. 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.
    9. Haiko Lietz, 2020. "Drawing impossible boundaries: field delineation of Social Network Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2841-2876, December.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Monika Cerinšek & Vladimir Batagelj, 2015. "Network analysis of Zentralblatt MATH data," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 977-1001, January.
    15. de Paulo, Alex Fabianne & Nunes, Breno & Porto, Geciane, 2020. "Emerging green technologies for vehicle propulsion systems," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    16. Jung, Sukhwan & Yoon, Wan Chul, 2020. "An alternative topic model based on Common Interest Authors for topic evolution analysis," Journal of Informetrics, Elsevier, vol. 14(3).
    17. Vladimir Batagelj, 2020. "On fractional approach to analysis of linked networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 621-633, May.
    18. 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.
    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. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    21. 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.
    22. Daria Maltseva & Vladimir Batagelj, 2022. "Collaboration between authors in the field of social network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3437-3470, June.
    23. 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.

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