The “digitalization” of sociology: new opportunities and key contradictions
https://doi.org/10.24290/1029-3736-2024-30-4-145-163
Abstract
The article analyzes the impact of digitalization on sociology and the professional trajectories of a sociologist. The main stages of the “digitalization” of sociology are highlighted, within which not only the amount of data used changes, but also the methods of their processing and analysis. Speaking about the transformation of modern sociology, the author describes several projects of its “digitization”, defining the key features of each. The “digitalization” of sociology is considered as an ambivalent process, which, on the one hand, opens up a whole range of opportunities for the researcher, on the other, actualizes a number of serious problems. The development of computing technologies leads to the expansion of opportunities for rethinking and verification of individual classical theories, the widespread introduction of non-reactive methods of sociological research, to increase their evidence and reproducibility. At the same time, the problems of digitalization are: an increase in the “black box” effect, bias and opacity of artificial intelligence algorithms, a decrease in the interpretability of the results obtained by a sociologist working in the “big data” paradigm. This leads to the need to rethink the model of Russian sociological education, the development of educational technologies that integrate classical sociological thinking and new digital technologies.
About the Author
V. A. SmirnovRussian Federation
Smirnov Vladimir A., Doctor of Sociology, Associate Professor, Associate Professor of the Department of Contemporary Sociology, Faculty of Sociology
Moscow
Leninsky Gory, 1-33, Moscow, 119234
References
1. Chambers J.M. Programming with Data: a guide to the S language. L., 1998.
2. Christakis N.A., Fowler J.H. Social contagion theory: examining dynamic social networks and human behavior // Statistics in Medicine. 2013. Vol. 32. N 4. P. 556–577.
3. Davydov A.A. Komp’yuternye tekhnologii dlya sociologii: obzor zarubezhnogo opyta [Computer technologies for sociology: a review of foreign experience] // Sociologicheskie issledovaniya. 2005. N 1. C. 131–138 (in Russian).
4. DiMaggio P., Nag M., Blei D. Exploiting affinities between topic modeling and the sociological perspective on culture: application to newspaper coverage of U.S. Government arts funding // Poetics. 2013. Vol. 41. N 6. P. 570–606.
5. Edelmann A., Wolff T., Montagne D., Bail C. Computational social science and sociology // Annual Review of Sociology. 2020. Vol. 46. N 1. P. 61–81.
6. Goroshnikova T.A. Vychislitel’naya sociologiya: sdvig paradigmy ili “ekonometrika” sociologii [Computational sociology: a paradigm shift or “eco-metrics” of sociology] // Gumanitarnye nauki. Vestnik Finansovogo universiteta. 2021. T. 11. N 1. S. 37–42. DOI: 10.26794/2226-7867-2021-11-1-37-42 (in Russian).
7. Guba K. Bol’shie dannye v sociologii: novye dannye, novaya sociologiya? [Big data in sociology: new data, new sociology?] // Sociologicheskoe obozrenie. 2018. T. 17. N 1. S. 213–236 (in Russian).
8. Karen G., Cottom T.M., Daniels J. Introduction // Digital Sociologies / Ed. by J. Daniels, G. Karen, T.M. Cottom. Chicago, 2017. P. xvii–xxx.
9. Kitchin R. Big Data, new epistemologies and paradigm shifts // Big Data & Society. 2014. Vol. 1. N 1. P. 1–12.
10. Latour B. Gabriel Tarde and the end of the social // The Social in Question. New Bearings in History and the Social Sciences / Ed. by P. Joyce. L., 2002. P. 117–132.
11. Lazer D., Pentland A. and et al. Computational social science // Science. 2009. Vol. 323. Iss. 5915. P. 721–722.
12. Lazer D.M.J., Pentland A. and et al. Computational social science: obstacles and opportunities // Science. 2020. Vol. 369. N 6507. P. 1060–1062.
13. Lupton D. Digital Sociology. N.Y., 2014.
14. Lupton D. Thinking with care about personal data profiling: a more-than-human approach // International Journal of Communication. 2020. Vol. 14.
15. Malyshev I.O., Smirnov A.A. Obzor sovremennyh generativnyh nejrosetej: otechestvennaya i zarubezhnaya praktika [Review of modern generative neural networks: domestic and foreign practice] // International Journal of Humanities and Natural Sciences. 2024. Vol. 1–2 (88). P. 168–171 (in Russian).
16. Mamedov A.K. Dekonstrukciya kul’turnogo prostranstva: smert’ teksta [Deconstruction of cultural space: the death of text] // Vestnik Moskovskogo universiteta. Seriya 18. Sociologiya i politologiya. 2021. T. 27. N 3. S. 152–166 (in Russian).
17. McAbee S.T., Landis R.S., Burke M.I. Inductive reasoning: the promise of Big Data // Human Resource Management Review. 2017. Vol. 27. N 2. P. 277–290.
18. Mohr J.W., Wagner-Pacifici R., Breiger R.L., Bogdanov P. Graphing the grammar of motives in national security strategies: cultural interpretation, automated text analysis and the drama of global politics // Poetics. 2013. Vol. 41. N 6. P. 670–700.
19. Neil S. What is digital sociology? Cambridge, 2019. Moiseev S., Staf M. “There’s an AI for that”: vozmozhnosti ChatGPT dlya raboty s otkrytymi istochnikami dannyh [“There’s an AI for that”: ChatGPT capabilities for working with open data sources] // Sociodigger. 2023. T. 4. Vyp. 7–8(27). URL: https://sociodigger.ru/articles/articles-page/theres-an-ai-for-that-vozmozhnosti-chatgpt-dlja-raboty-s-otkrytymi-istochnikami-dannykh (data obrashcheniya: 15.07.2024) (in Russian).
20. Nikolaenko G.A., Fedorova A.A. Nereaktivnaya strategiya: primenimost’ nezametnyh metodov sbora sociologicheskoj informacii v usloviyah Web 2.0 na primere cifrovoj etnografii i Big Data [Non-reactive strategy: the applicability of unnoticeable methods of collecting sociological information in the context of Web 2.0 using digital ethnography and Big Data as an example] // Sociologiya vlasti. 2017. T. 29 (4). S. 36–54 (in Russian).
21. Noortje M. Digital sociology: the reinvention of social research. Cambridge, 2017.
22. Osipova N.G. Cifrovizaciya social’noj real’nosti: klyuchevye diskussii [Digitalization of social reality: key discussions] // Vestnik Moskovskogo universiteta. Seriya 18. Sociologiya i politologiya. 2022. T. 28. N 3. S. 4. DOI: https://doi. org/10.24290/1029-3736-2022-28-3-9-42 (in Russian).
23. Paskvinelli M. Izmeryat’ i navyazyvat’. Social’naya istoriya iskus-stvennogo intellekta [Measure and impose. Social history of artificial intelligence]. M., 2024 (in Russian).
24. Rozado D. The political biases of chatgpt // Social Sciences. 2023. Vol. 12. N 3.
25. Savage M., Burrows R. The coming crisis of empirical sociology // Sociology. 2007. N 41 (5). Р. 885–899.
26. Seale J., Charteris-Black A. Interviews and internet forums: a comparison of two sources of qualitative data // Qualitative Health Research. 2010. Vol. 20. P. 595–606.
27. Smirnov V.A. Novye kompetencii sociologa v epohu bol’shih dannyh [New competencies of a sociologist in the era of big data] // Monitoring obshchestvennogo mneniya: ekonomicheskie i social’nye peremeny. 2015. N 2. S. 44–54. DOI: 10.14515/ monitoring.2015.2.04 (in Russian).
28. Sorokin P.A. Social’naya i kul’turnaya dinamika [Social and cultural dynamics]. M., 2006 (in Russian).
29. Tard G. Social’nye zakony [Social Laws] // Sociologiya / Sost. V. Zombart. M., 2003 (in Russian).
30. Tolstova Yu.N. Izmerenie v sociologii [Measurement in Sociology]. M., 2009 (in Russian).
31. Tolstova Yu.N. Sociologiya i komp’yuternye tekhnologii [Sociology and Computer Technologies] // Sociologicheskie issledovaniya. 2015. N 8. S. 3–13 (in Russian).
32. Uikem H., Groulmund G. Yazyk R v zadachah nauki o dannyh: import, podgotovka, obrabotka, vizualizaciya i modelirovanie dannyh [The R Language in Data Science Tasks: Import, Preparation, Processing, Visualization, and Modeling of Data]. M., 2017 (in Russian).
33. Vershinina I.A., Lyadova A.V. Dannye v cifrovom mire: novye vozmozhnosti ili dopolnitel’nye riski? [Data in the digital world: new opportunities or additional risks?] // Vestnik Rossijskogo universiteta druzhby narodov. Seriya: Sociologiya. 2020. T. 20. N 4. C. 977–984. DOI: 10.22363/2313-2272-2020-20-4-977-984 (in Russian).
34. Webb E., Campbell D., Schwartz R. Unobtrusive measures: nonreactive research in the social sciences. Chicago, 1966.
35. Wellman B. Doing it ourselves: the SPSS manual as sociology’s most influential recent book // Required Reading: Sociology’s Most Influential Books / Ed. by D. Clawson. Amherst, 1998. P. 71–78.
36. Wynn J.R. Digital sociology: emergent technologies in the field and the classroom // Sociological Forum. 2009. Vol. 24. P. 448–456.
Review
For citations:
Smirnov V.A. The “digitalization” of sociology: new opportunities and key contradictions. Moscow State University Bulletin. Series 18. Sociology and Political Science. 2024;30(4):146-164. (In Russ.) https://doi.org/10.24290/1029-3736-2024-30-4-145-163