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Social network analysis as a field of invasions: bibliographic approach to study SNA development

Author

Listed:
  • Daria Maltseva

    (National Research University Higher School of Economics)

  • Vladimir Batagelj

    (National Research University Higher School of Economics
    Institute of Mathematics, Physics and Mechanics
    University of Primorska)

Abstract

In this paper, the results of a study on the development of social network analysis (SNA) and its evolution over time, using the analysis of bibliographic networks are presented. The dataset consists of articles from the Web of Science Clarivate Analytics database obtained by searching for the keyword “social network*” and those published in the main journals in the field (in total 70,000+ publications). From the data, we constructed several networks. In this paper, the focus is on the analysis of the citation network. Analyzing the obtained network, we evaluated the SNA field’s growth and identified the most cited works. Using the normalized Search path count weights, we extracted the main path, key-route paths, and link islands in the citation network. Based on the probabilistic flow node values, we also identified the most important articles. Our results show that the number of published papers almost doubles each 3 years. We confirmed the finding that the authors from the social sciences, who were most active through the whole history of the field development, experienced the “invasion” of physicists from the 2000s. However, starting from the 2010s, a new very active group of animal social network analysts took the leading position.

Suggested Citation

  • Daria Maltseva & Vladimir Batagelj, 2019. "Social network analysis as a field of invasions: bibliographic approach to study SNA development," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 1085-1128, November.
    • Handle: RePEc:spr:scient:v:121:y:2019:i:2:d:10.1007_s11192-019-03193-x
    DOI: 10.1007/s11192-019-03193-x
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    References listed on IDEAS

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    1. Lovro Šubelj & Dalibor Fiala, 2017. "Publication boost in web of science journals and its effect on citation distributions," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 1018-1023, April.
    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. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    4. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    5. Anne-Wil Harzing & Satu Alakangas, 2016. "Google Scholar, Scopus and the Web of Science: a longitudinal and cross-disciplinary comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 787-804, February.
    6. Martín-Martín, Alberto & Orduna-Malea, Enrique & Thelwall, Mike & Delgado López-Cózar, Emilio, 2018. "Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories," Journal of Informetrics, Elsevier, vol. 12(4), pages 1160-1177.
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    Citations

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    Cited by:

    1. Dejian Yu & Zhaoping Yan, 2021. "Knowledge diffusion of supply chain bullwhip effect: main path analysis and science mapping analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8491-8515, October.
    2. Aryuna Kim & Daria Maltseva, 2024. "Qualitative social network analysis: studying the field through the bibliographic approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 385-411, February.
    3. 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.
    4. Flavia Filippin, 2021. "Do main paths reflect technological trajectories? Applying main path analysis to the semiconductor manufacturing industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6443-6477, August.
    5. Daria Maltseva & Vladimir Batagelj, 2021. "Journals publishing social network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3593-3620, April.
    6. 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.
    7. Haiko Lietz, 2020. "Drawing impossible boundaries: field delineation of Social Network Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2841-2876, December.
    8. Martin Ho & Henry CW Price & Tim S Evans & Eoin O'Sullivan, 2023. "Order in Innovation," Papers 2302.13076, arXiv.org.
    9. 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.

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    More about this item

    Keywords

    Development of scientific fields; Social network analysis; Citation network; Search path count; Probabilistic flow; Web of science;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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