Skip to main content
SpringerLink
Log in

Towards a systematic description of the field using keywords analysis: main topics in social networks

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

This paper presents the results of the analysis of keywords used in Social Network Analysis (SNA) articles included in the WoS database and main SNA journals, from 1970 to 2018. 32,409 keywords were obtained from 70,792 works with complete descriptions. We provide a list of the most used keywords and show subgroups of keywords which are connected to each other. To go deeper, we place the keywords into the contexts of selected groups of authors and journals. We use temporal analysis to get an insight into some keyword usage. The distributions of the number of keyword types and tokens over time show fast growth starting from 2010s, which is the result of the growth in the number of articles on SNA topics and applications of SNA in various scientific fields. Even though the most frequently used keywords are trivial or general, the approaches used for the normalization of network link weights allow us to extract keywords representing substantive topics and methodological issues in SNA.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Batagelj, V. (2014). Nets—Python package for network analysis. Available at: https://github.com/bavla/Nets/tree/master/source.

  • Batagelj, V. (2017). WoS2Pajek. Networks from Web of Science. Version 1.5 (2017). Available at: http://vladowiki.fmf.uni-lj.si/doku.php?id=pajek:wos2pajek.

  • Batagelj, V. (2019). On fractional approach to analysis of linked networks. Available at: arxiv:1903.00605.

  • Batagelj, V., & Maltseva, D. (2020). Temporal bibliographic networks. Journal of Informetrics. https://doi.org/10.1016/j.joi.2020.101006 

  • Batagelj, V., & Cerinšek, M. (2013). On bibliographic networks. Scientometrics, 96(3), 845–864.

    Article  Google Scholar 

  • Batagelj, V., Doreian, P., Ferligoj, A., & Kejžar, N. (2014). Understanding large temporal networks and spatial networks: Exploration, pattern searching, visualization and network evolution. Chichester: Wiley.

    Book  Google Scholar 

  • Batagelj, V., Ferligoj, A., & Doreian, P. (2020). Bibliometric analysis of the network clustering literature. In P. Doreian, V. Batagelj, & A. Ferligoj (Eds.), Advances in network clustering and blockmodeling (pp. 63–102). Hoboken, NJ: Wiley.

    Google Scholar 

  • Batagelj, V., Ferligoj, A., & Squazzoni, F. (2017). The emergence of a field: A network analysis of research on peer review. Scientometrics, 113, 503–532.

    Article  Google Scholar 

  • Batagelj, V., & Praprotnik, S. (2016). An algebraic approach to temporal network analysis based on temporal quantities. Social Network Analysis and Mining, 6(1), 1–22.

    Article  Google Scholar 

  • Bonacich, P. (2004). The invasion of the physicists. Social Networks, 26, 285–288.

    Article  Google Scholar 

  • Borgatti, S. P., & Foster, P. C. (2003). The network paradigm in organizational research: A review and typology. Journal of Management, 29(6), 991–1013.

    Article  Google Scholar 

  • Brandes, U., & Pich, C. (2011). Explorative visualization of citation patterns in social network research. Journal of Social Structure, 12(8), 1–19.

    Google Scholar 

  • Freeman, L. C. (2004). The development of social network analysis. A study in the sociology of science. Vancouver, BC: Empirical Press.

    Google Scholar 

  • Freeman, L. C. (2011). The development of social network analysis-with an emphasis on recent events. The SAGE Handbook of Social Network Analysis, 21(3), 26–39.

    Google Scholar 

  • Gauffriau, M., Larsen, P., Maye, I., Roulin-Perriard, A., & von Ins, M. (2007). Publication, cooperation and productivity measures in scientific research. Scientometrics, 73(2), 175–214.

    Article  Google Scholar 

  • Hummon, N. P., & Carley, K. (1993). Social networks as normal science. Social Networks, 15(1), 71–106.

    Article  Google Scholar 

  • Hummon, N. P., Doreian, P., & Freeman, L. C. (1990). Analyzing the structure of the centrality-productivity literature created between 1948 and 1979. Science Communication, 11(4), 459–480.

    Google Scholar 

  • Kejžar, N., Černe, S. K., & Batagelj, V. (2010). Network analysis of works on clustering and classification from web of science. Classification as a tool for research (pp. 525–536). Berlin, Heidelberg: Springer.

  • Lazer, D., Mergel, I., & Friedman, A. (2009). Co-citation of prominent social network articles in sociology journals: The evolving canon. Connections, 29(1), 43–64.

    Google Scholar 

  • Leydesdorff, L., Schank, T., Scharnhorst, A., & De Nooy, W. (2008). Animating the development of Social networks over time using a dynamic extension of multidimensional scaling. El Profesional de Informacion. https://doi.org/10.3145/epi.2008.nov.04.

    Article  Google Scholar 

  • Maltseva, D., & Batagelj, V. (2019). Social network analysis as a field of invasions: Bibliographic approach to study SNA development. Scientometrics, 121(2), 1085–1128. https://doi.org/10.1007/s11192-019-03193-x.

    Article  Google Scholar 

  • Newman, M. E. (2001). Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E, 64(1), 016132.

    Article  MathSciNet  Google Scholar 

  • Otte, E., & Rousseau, R. (2002). Social network analysis: A powerful strategy, also for the information sciences. Journal of Information Science, 28(6), 441–453.

    Article  Google Scholar 

  • Robertson, S. (2004). Understanding inverse document frequency: On theoretical arguments for IDF. Journal of Documentation, 60(5), 503–520.

    Article  Google Scholar 

  • Varga, A. V., Nemeslaki, A. (2012). Do organizational network studies constitute a cohesive communicative field? Mapping the citation context of organizational network research. Journal of Sociology and Social Anthropology 5(64), XV: 349–364.

Download references

Acknowledgements

We would like to express our special gratitude to our colleague, professor Anuška Ferligoj (University of Ljubljana and the International Laboratory for Applied Network Research, Moscow) for her advice and comments which greatly improved the manuscript. We appreciate the help of David Connolly (Academic Writing Center, Higher School of Economics, Moscow) with the proofreading of the article. This work is supported in part by the Slovenian Research Agency (Research Program P1-0294 and Research Projects J1-9187 and J7-8279), project COSTNET (COST Action CA15109), and by Russian Academic Excellence Project ’5-100’. The funding sources had no involvement in the study and article.

Author information

Authors and Affiliations

  1. National Research University Higher School of Economics, 11 Pokrovsky Boulevard, Moscow, Russia, 101000

    Daria Maltseva & Vladimir Batagelj

  2. Institute of Mathematics, Physics and Mechanics, Jadranska 19, 1000, Ljubljana, Slovenia

    Vladimir Batagelj

  3. University of Primorska, Andrej Marušič Institute, 6000, Koper, Slovenia

    Vladimir Batagelj

Authors
  1. Daria Maltseva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vladimir Batagelj
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daria Maltseva.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Maltseva, D., Batagelj, V. Towards a systematic description of the field using keywords analysis: main topics in social networks. Scientometrics 123, 357–382 (2020). https://doi.org/10.1007/s11192-020-03365-0

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-020-03365-0

Keywords

Search

Navigation