IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v14y2020i1s1751157719301439.html
   My bibliography  Save this article

Temporal bibliographic networks

Author

Listed:
  • Batagelj, Vladimir
  • Maltseva, Daria

Abstract

We present two ways (instantaneous and cumulative) to transform bibliographic networks, using the works’ publication year, into corresponding temporal networks based on temporal quantities. We also show how to use the addition of temporal quantities to define interesting temporal properties of nodes, links and their groups thus providing an insight into evolution of bibliographic networks. Using the multiplication of temporal networks we obtain different derived temporal networks providing us with new views on studied networks. The proposed approach is illustrated with examples from the collection of bibliographic networks on peer review.

Suggested Citation

  • Batagelj, Vladimir & Maltseva, Daria, 2020. "Temporal bibliographic networks," Journal of Informetrics, Elsevier, vol. 14(1).
    • Handle: RePEc:eee:infome:v:14:y:2020:i:1:s1751157719301439
    DOI: 10.1016/j.joi.2020.101006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157719301439
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2020.101006?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. Monika Cerinšek & Vladimir Batagelj, 2015. "Network analysis of Zentralblatt MATH data," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 977-1001, January.
    2. 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.
    3. Vladimir Batagelj & Monika Cerinšek, 2013. "On bibliographic networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 845-864, September.
    4. Petter Holme, 2015. "Modern temporal network theory: a colloquium," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(9), pages 1-30, 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. Vladimir Batagelj, 2024. "On weighted two-mode network projections," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3565-3571, June.
    2. 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.
    3. Daria Maltseva & Vladimir Batagelj, 2021. "Journals publishing social network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3593-3620, April.
    4. Tošić, Aleksandar & Vičič, Jernej, 2021. "Use of Benford's law on academic publishing networks," Journal of Informetrics, Elsevier, vol. 15(3).
    5. 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.

    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. 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.
    2. 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.
    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. Daria Maltseva & Vladimir Batagelj, 2021. "Journals publishing social network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3593-3620, April.
    5. 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.
    6. Anzhi Sheng & Qi Su & Aming Li & Long Wang & Joshua B. Plotkin, 2023. "Constructing temporal networks with bursty activity patterns," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    7. Panayotis Christidis & Álvaro Gomez Losada, 2019. "Email Based Institutional Network Analysis: Applications and Risks," Social Sciences, MDPI, vol. 8(11), pages 1-14, November.
    8. 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.
    9. Dantsuji, Takao & Sugishita, Kashin & Fukuda, Daisuke, 2023. "Understanding changes in travel patterns during the COVID-19 outbreak in the three major metropolitan areas of Japan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    10. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    11. Hongyong Wang & Ping Xu & Fengwei Zhong, 2022. "Modeling and Feature Analysis of Air Traffic Complexity Propagation," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    12. Balázs Győrffy & Andrea Magda Nagy & Péter Herman & Ádám Török, 2018. "Factors influencing the scientific performance of Momentum grant holders: an evaluation of the first 117 research groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 409-426, October.
    13. Abdelghani Maddi, 2018. "Analyse scientométrique de la crise économique," CEPN Working Papers 2018-08, Centre d'Economie de l'Université de Paris Nord.
    14. Pietro DeLellis & Anna DiMeglio & Franco Garofalo & Francesco Lo Iudice, 2017. "The evolving cobweb of relations among partially rational investors," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-21, February.
    15. 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.
    16. 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.
    17. Monika Cerinšek & Vladimir Batagelj, 2015. "Network analysis of Zentralblatt MATH data," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 977-1001, January.
    18. Mathilde Vernet & Yoann Pigné & Éric Sanlaville, 2023. "A study of connectivity on dynamic graphs: computing persistent connected components," 4OR, Springer, vol. 21(2), pages 205-233, June.
    19. Karan, Rituraj & Biswal, Bibhu, 2017. "A model for evolution of overlapping community networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 380-390.
    20. 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.

    More about this item

    Keywords

    Social network analysis; Temporal networks; Linked networks; Bibliographic networks; Temporal quantities; Semiring; Network multiplication; Fractional approach;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

    Statistics

    Access and download statistics

    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:eee:infome:v:14:y:2020:i:1:s1751157719301439. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    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.