Methodology of big data in studying orthodox communities
The article discusses the emergence of "digital sociology" as a new scientific direction, its main methodological principles, and their implementation in empirical research in the social network VKontakte. The working process of the researcher with such a tool as a data parser is considered, as well as the main principles of using this method.
Within the framework of the "big data" paradigm, we analyze the principles of building a study sample, including the selection of communities and their participants. Using the example of Orthodox VKontakte communities dedicated to the family, we show such techniques for minimizing the sampling error and selecting the most relevant audience, as searching for users in selected communities; finding users in several communities at the same time, which contributes to the uniformity of the sample; clearing bots and users who have not installed an avatar; searching for users with an "open" date of birth.
The article identifies socio-demographic criteria for analyzing the audience of Orthodox communities (distribution by gender and age groups, geography of community members by country and city, marital status, number of children), as well as the main behavioral criterion – the engagement rate.
The engagement rate as a research tool allows to take into account the behavioral activity of community members, including likes, republications, and comments over the entire lifetime of certain communities. This criterion allows you to assess the degree of influence of communities on their members, based not on the number of VKontakte groups, which may differ at times, but on the degree of participation of subscribers in the life of the community. The article shows that the engagement rate in Orthodox family communities is higher on average than in secular communities of similar subjects. This is primarily due to the very religious orientation of Orthodox communities, which allows both active engagement of existing subscribers in various communication activities, and involvement of new ones.
Information for citation: Pisarevskiy, V. G. (2020), “Methodology of big data in studying orthodox communities”, Research Result. Sociology and management, 6 (1), 16-28. DOI: 10.18413/2408-9338-2020-6-1-0-2
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Akhmetov, S. (2018), "Big data: where to start", available at: https: //VK.ru/flood/37763-big-date-with-what-to-start (Accessed 1 January 2020).
Volkov, A. "How to clear the database of bots?", available at: https://vk.com/evo_marketing?w=page-41179708_51894717/ (Accessed 1 January 2020).
Brand Analytics Blog (2018), "Social networks in Russia: figures and trends, autumn 2018", available at: https://br-analytics.ru/blog/socseti-v-rossii-osen-2018/ (Accessed 2 January 2020).
Castells, M. (2020), "Our life is a hybrid of virtual and physical space", available at: http://ria.ru/interview/20120622/679289114.html (Accessed 02 January 2020).
Castells, M. (2004), The Internet Galaxy: Reflections on Internet, business and society, Translated by Matveev, A., U-Factoriya, Yekaterinburg, Russia.
Demis Group (2020), "Features of the VKontakte audience", available at: https://www.demis.ru/articles/celevaya-auditoria-VKontakte / (Accessed 3 January 2020).
VKontakte (2020), "Official VKontakte social network statistics", available at: https://vk.com/about (Accessed 3 January 2020).
Pisarevskiy, V. (2016), "Orthodox communities in the Internet resource space and their impact on social networks", Ph.D. Thesis, Institute of sociology of Russian academy of sciences, Moscow, Russia.
Russ, K. (2015), "Lent in Russia": statistics. Conversation with analysts of the research service "Wednesday", available at: http://www.pravoslavie.ru/jurnal/78328.htm (Accessed 04 January 2020)
VKontakte (2020), "Search service audience in social networks "target hunter", available at: https://vk.targethunter.ru (Accessed 4 January 2020)
Baym, B. K. (2013), "The data not seen: the uses and shortcomings of social media metrics", First Monday [Electronic], 10-7, vol. 18, available at: http://firstmonday.org/ojs/index.php/fm/article/view/4869/3750, (Accessed 5 January 2020)
Boyd, D. and Crawford, K. (2012), "Critical questions for big data", Information, communication and society, 15 (5), 662-679.
Boellstorff, T. (2013), "The creation of big data, in theory", First Monday [Electronic], 10-7, vol. 18, available at: http://firstmonday.org/ojs/index.php/fm/article/view/4869/3750 (Accessed 5 January 2020).
Carrigan, M. (2013), "What is digital sociology?", available at: HTTP://markcarrigannet/2013/01/12/что-это-цифровой-социология/ (Accessed 11 January 2020).
Castells, M. (2009), Communication power, Oxford University Press, Oxford, UK.
Kavanagh, A. (2007), Sociology in the Internet age, Open University Press, Berkshire, UK.
Crawford, K. (2013), "Hidden biases of big data", Harvard business review [Electronic], available at: https://hbr.org/2013/04/the-hidden-biases-in-big-data (Accessed 1 January 2020).
Couldry, N. and Fotopoulou, A. (2014), "Social Analytics: Digital phenomenology in the face of algorithmic power", available at: http://www.emeraldinsight.com/doi/full/10.1108/S1042-319220140000013002 (Accessed 9 January 2020).
Hand, M. (2014), Big data?Qualitative approach to digital research, Emerald Publishing.
Ruka, M. (2014), Digitization and memory: a study of practices for adapting to visual and textual data in everyday life, available at: https://www.researchgate.net/publication/289398324_Digitization_and_Memory_Researching_Practices_of_Adaption_to_Visual_and_Textual_Data_in_Everyday_Life, (Accessed 9 January 2020).
Kitchin, R. (2014), The Data Revolution: big data, open data, data infrastructures and their consequences, Sage, London, UK.
Lupton, D. (2012), Digital sociology: An introduction, University Of Sydney, Sydney, Australia.
Lupton, D. (2020), "Toward a Manifesto for public understanding of big data", available at: https://www.researchgate.net/publication/282871735_Toward_a_manifesto_for_the_'public_understanding_of_big_data' (Accessed 13 January 2020).
Lupton, D. (2015), Digital sociology, Routledge, London, UK.
Mayer-Schonberger, V. and Cukier, K. (2013), Big data: a revolution that will change the way we live, work, and think, John Murray, Lindon, UK.
Marres, N. (2012), "Redistribution of methods: on intervention in digital social research, widely conceived, Sociological Review Sociological commentary, 60, 139-165.
Orton-Johnson, K. and Prior, N. (2013), Digital sociology – critical perspectives, Palgrave Macmillan, London, UK.
Rogers (2013), Digital methods, MIT Press, Cambridge, MA, UK.
Ruppert, E., Law, J. and Savage, M. (2013), "Reassembling social science methods: the challenge of digital devices", available at: http://in the TCS.sagepub.com / content/start/2013/05/13/0263276413484941.multi-selection (Accessed 15 January 2020).