Sociology of values: experience of building a taxonomy by using natural language analysis technology

Modern research in the field of sociology of science is becoming more complicated due to the constantly growing publication activity of authors. To track trends in sectoral sociology, scientists turn to scientometric methods, but they are not enough. Trends in the development of the sociology of values as a branch of sociology are the subject of the study. The purpose of the work is an assessment of the possibilities of using natural language analysis methods (NLP/NLA) for thematic and theoretical clustering of research in the sociology of values. The design of the study was quantitative and qualitative, it was carried out in two stages. At the first stage, 121 abstracts of a scientific articles were analyzed using text mining, after which their total array was divided into clusters. At the second stage, the results of machine clustering were examined by the method of qualitative text analysis, on the basis of which the limitations and capabilities of the NLP/NLA method were identified for solving the problem of clustering scientific texts. It was found that articles with a more conservative core of theoretical categories (gender studies, migration studies, the theory of globalism) are more amenable to clustering, while theories with a loosely structured and fluid theoretical core (theories using environmental terminology, theories of inequality) are much less amenable to explicit clustering. The results obtained allow us to form a new direction of work with large arrays of scientific texts, associated with their clustering using NLP/NLA. Building clusters enables researchers to work with all texts in a given subject area, and not just with the most cited ones. This, in turn, provides the visibility of all scientific ideas, including those that have not gained popularity/notability.

1. Alexandrov D.A. (1998), “Scientific schools as social networks” [“Nauchnye shkoly kak sotsial’nye seti”], Academic scientific schools of St. Petersburg. To the 275th anniversary of the Academy of Sciences, St. Petersburg Scientific Center of the Russian Academy of Sciences, St. Petersburg, Russia, pp. 11–18 (in Russian).

2. Arnarsson I.Ö., Frost O., Gustavsson E., Jirstrand M., Malmqvist J. (2021), “Natural language processing methods for knowledge management –Applying document clustering for fast search and grouping of engineering documents”, Concurrent Engineering Research and Applications, vol. 29, no. 2, pp. 142–152, https://doi.org/10.1177/1063293X20982973

3. Black M. (1955), “Metaphor. Proceedings of the Aristotelian Society”, New Series, vol. 55, pp. 273–29.

4. Bourdieu P. (2020), Habitus and Field: General Sociology, volume 2 (1982–1983), Wiley, NJ, USA.

5. Calambas M.A., Ordonez A., Chacon A., Ordonez H. (2015), “Judicial precedents search supported by natural language processing and clustering”, 10th Colombian Computing Conference, 10CCC (2015), art. no. 7333448, pp. 372–377, https://doi.org/10.1109/ColumbianCC.2015.7333448

6. Collins H., Evans R. (2007), Rethinking expertise, University of Chicago Press, Chicago, US.

7. Collyer F. (2011), “Reflexivity and the sociology of science and technology: The invention of ‘Eryc’ the antibiotic”, Qualitative Report, vol. 16, no. 2, pp. 316–340.

8. Foucault M. (2002), Archaeology of knowledge, Routledge, London, New York.

9. Kashina M.A., Lyashko S.V., Tkach S. (2021), “Topical agenda for the study of values in foreign sociology: topics, theories, methodologies”, Administrative Consulting, no. 10, pp. 62–82, https://doi.org/10.22394/1726-1139-2021-10-62-82 (in Russian).

10. Kononenko, E.I. (2021), “Once again about simulation of scientific activity in the humanities”, Vestnik of Saint Petersburg University. Arts, vol. 11, no. 2, pp. 327–349, https://doi.org/10.21638/spbu15.2021.209 (in Russian).

11. Lakoff G., Johnson M. (1980), Metaphors we live by, University of Chicago Press, Chicago, US.

12. Latour B. (1987), Science in action: how to follow scientists and engineers through society, Harvard University Press, Cambridge, Mass., US.

13. Liu S., Emirbayer M. (2016), “Field and ecology”, Sociological Theory, vol. 34, no. 1, pp. 62–79.

14. Lyotard J. F. (1997), The postmodern condition, University of Minnesota, Minnesota, US.

15. Maksimenko A.A. (2011), “Sociological interpretation of ‘value’ concept” [“Sotsiologicheskaya interpretatsiya ponyatiya ‘Tsennost’”], Vestnik of Kostroma State University, vol. 17, no. 2, pp. 284–291 (in Russian).

16. McDonald S.P., Kelly G.J. (2012), “Beyond argumentation: Sense-making discourse in the science classroom”, Perspectives on Scientific Argumentation: Theory, Practice and Research, vol. 9789400724709, pp. 265–281, https://doi.org/10.1007/978-94-007-2470-9_13

17. Merton R.K. (1979), “The Normative Structure of Science”, In: The Sociology of Science: Theoretical and Empirical Investigations, University of Chicago Press, Chicago, US.

18. Schneider J.W. (2013), “Caveats for using statistical significance tests in research assessments”, Journal of Informetrics, vol. 7, no. 1, pp. 50–62.

19. Shutova E., Kiela D., Maillard J. (2016), “Black holes and white rabbits: Metaphor identification with visual features”, 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 – Proceedings of the Conference, pp. 160–170, http://dx.doi.org/10.18653/v1/N16-1020

20. Spates James L. (1983), “The sociology of values”, Annual Review of Sociology, vol. 9, pp. 27–49.

21. Tao R., Wei Y., Yang T. (2021), “Metaphor analysis method based on latent semantic analysis”, Journal of Donghua University (English Edition), vol. 38, no. 1, pp. 83–90, http://dx.doi.org/10.1016/S1532-0464(02)00004-7

22. Weber M. (1990), Selected works [Izbrannye proizvedeniya], Trans. from Germ. and Ed. Davydov Yu.N. Progress, Moscow, Russia (in Russian).

23. Young T., Hazarika D., Poria S., Cambria E. (2018). “Recent trends in deep learning based natural language processing” [Review Article], IEEE Computational Intelligence Magazine, vol. 13, no. 3, art. no. 8416973, pp. 55–75, https://doi.org/10.48550/arXiv.1708.02709

24. Yudina M.A. (2017), “Industry 4.0: prospects and challenges for Society” [“Industriya 4.0: perspektivy i vyzovy dlya obshchestva”], Public Administration. E-journal (Russia), no. 60, pp. 197–215 (in Russian).

25. Zinnatullin V., Koledin S. (2020), “Analysis of scientists work directions based on natural language processing and clustering”, CEUR Workshop Proceedings, no. 2667, pp. 57–61.

26. Žižek S., Damià A. (2020), Pandemic: covid-19 shakes the world [Pandemia: la covid-19 estremece al mundo], Editorial Anagrama, Barcelona (in Spanish).