Reassembling Sociology: Digital Turn and Searching for New Theoretical Optics

 
PIIS013216250016830-6-1
DOI10.31857/S013216250016829-4
Publication type Article
Status Published
Authors
Occupation: Associate Professor
Affiliation: St. Petersburg State University
Address: Russian Federation, St. Petersburg
Journal nameSotsiologicheskie issledovaniya
EditionIssue 11
Pages3-11
Abstract

With the growth of the methodological possibilities of research using digital data in sociology, there is a need for theoretical model corresponding to digital research tools. The aim of the article is to reconstruct possible theoretical optics for sociology from the point of view of the more effective use of digital methods and data analytical potential. The article attempts to outline such a theoretical model corresponding to digital research tools. Based on the thesis about the dependence of theories on methodological research tools, the idea of turning digital traces into an independent object of social research is developed. The concept of replications, proposed by the French sociologist Dominique Boullier and rooted in the sociology of Gabriel Tarde, is viewed as a promising theoretical framework for conceptualizing digital traces. The theoretical optics of digital traces as replications is interpreted as the basis for rethinking the micro-macro problem.

Keywordsdigital data, digital traces, sociological theory, structure, replications, actor-network theory, Tarde, Latour
AcknowledgmentThe paper is funded by Russian Foundation for Basic Research (project 19-011-00905 A).
Received23.11.2021
Publication date22.12.2021
Number of characters28984
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1. Guba K. (2018) Big Data in Sociology: New Data, New Sociology? Sotsiologicheskoye obozreniye [Russian Sociological Review]. No. 1: 213–236. (In Russ.)

2. Deviatko I.F. (2016) From «Virtual Lab» to «Social Telescope»: Metaphors of Theoretical and Methodological Innovations in Online Research. In: Online-research in Russia: Trends and Prospects. Ed. by A.V. Shashkin, I.F. Deviatko, S.G. Davydov. Moscow: Tipografiya: 19–33. (In Russ.)

3. Dudina V.I., Iudina D.I. (2017) Mining opinions on the Internet: can text analysis methods replace public opinion polls? Monitoring obshchestvennogo mneniya: ekonomicheskiye i sotsial'nyye peremeny [Monitoring of Public Opinion: Economic and Social Change]. No. 5: 63–78. (In Russ.)

4. Latour B. (2014) Reassembling the social. An Introduction to Actor-Network-Theory. Moscow: NIU VSHE. (In Russ.)

5. Tarde G. (2011) Laws of imitation. Moscow: Academ. project. (In Russ.)

6. Tarde G. (2016) Monadology and Sociology. Perm: Gyle Press. (In Russ.)

7. Achim E., Wolff T., Montagne D., Bail C. (2020) Computational Social Science and Sociology. Annual Review of Sociology. No. 46: 61–81.

8. Bail C. (2014) The Cultural Environment: Measuring Culture with Big Data. Theory and Society. No. 43 (34): 465– 482.

9. Boullier D. (2016) Big Data Challenges for the Social Sciences: From Society and Opinion to Replications. arXiv.org. 18 July. URL: https: // arxiv.org/abs/1607.05034 (accessed 30.08.21).

10. Boullier D. (2019) Replications in Quantitative and Qualitative Methods: a New Era for Commensurable Digital Social Sciences. URL: https://arxiv.org/abs/1902.05984v1 (accessed 30.08.21).

11. Bowker G. C. (2014) The Theory/Data Thing Commentary. International Journal of Communication. No. 8 (2043): 1795–1799.

12. Centola D. (2010) The Spread of Behavior in an Online Social Network Experiment. Science. September (329): 1194–1197.

13. Centola D. (2018) How Behavior Spreads: The Science of Complex Contagions. Princeton: University Press.

14. Crumley C.L. (2015) Heterarchy. In: Emerging Trends in the Social and Behavioral Sciences: An Interdiscplinary, Searchable, and Linkable Resource. Ed. by Scott, R.A., Buchmann, M.C. Hoboken, NJ: Wiley: 1–14

15. DiMaggio P., Nag M., Blei D. (2013) Exploiting Affinities Between Topic Modeling and the Sociological Perspective on Culture: Application to Newspaper Coverage of U.S. Government Arts Funding. Poetics. No 41: 570–606.

16. Ignatow G. (2016) Theoretical Foundations for Digital Text Analysis. Journal for the Theory of Social Behaviour. Vol. 46. No. 1: 104–120.

17. Latour B. (2002) Gabriel Tarde and the End of the Social. In: Joyce P. (ed.) The Social in Question: New Bearings in the History and the Social Sciences. London: Routledge.

18. Latour B. (2010) Tarde’s Idea of Quantification. In: Candea M. (ed.) The Social after Gabriel Tarde: Debates and Assessments (Culture, Economy and the Social). Abingdon: Routledge: 145–163.

19. Latour B., Jensen P., Venturini T., Grauwin S., Boullier D. (2012) ‘The Whole is Always Smaller than Its Parts’: A Digital Test of Gabriel Tarde’s Monads. The British Journal of Sociology. Vol. 63. No. 4: 591–615.

20. Ledford H. (2020). How Facebook, Twitter and other data troves are revolutionizing social science. Nature. No. 7812: 328–330.

21. Marres N. (2017) Digital Sociology: The Reinvention of Social Research. Cambridge: Polity Press.

22. McFarland D., Lewis K., Goldberg A. (2015) Sociology in the era of big data: the ascent of forensic social science. American Sociologist. No. 47: 12–35.

23. Zhang J., Centola D. (2019) Social Networks and Health: New Developments in Diffusion, Online and Offline. Annual Review of Sociology. No. 45(1): 91–109.

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