Digital Demography Methods for Forecasting Migration Processes
DOI:
https://doi.org/10.17059/ekon.reg.2022-1-10Abstract
The nature and intensity of migration processes are constantly changing. Demographic statistics are not suitable for obtaining up-to-date information and making timely decisions in the field of demographic and social policy. Thus, digital demography is becoming increasingly important, as this area of population research uses new methods and data sources resulting from the Internet expansion and the digitalisation of society. Using digital demography methods and emerging data sources, the study aims to identify current migration trends in Russia at the municipal level. The duality of the object (real and virtual population) and methods (demographic and data science methods) of digital demography is demonstrated. Digital data sources for studying migration and relevant processing methods were considered. Further, it was proposed to assess migration flows by examining social network information and graphs of migration routes. The analysis of data obtained from the “Virtual population of Russia” project for 2356 urban and municipal regions revealed the features of inter-municipal migration and the centres of migration attraction in the country. An indicator for assessing the potential of future migrations based on the graphs of migration routes was presented. The analysis results show that balanced spatial development of Russia requires the stimulation of human capital development in local centres characterised by high migration potential. These include regional capitals, “second” cities in terms of population, and some research and industrial centres. The study findings can be used to consider demographic processes at the municipal level and elaborate strategic documents in the field of regional spatial development. Therefore, future research should focus on improving digital demography methods for studying and forecasting demographic processes.
References
Alburez-Gutierrez, D., Aref, S., Gil-Clavel, S., Grow, A., Negraia, D. V. & Zagheni, E. (2019). Demography in the Digital Era: New Data Sources for Population Research. In: SIS 2019. Smart statistics for smart applications (pp. 1–8). Milano: Pearson. DOI: 10.31235/osf.io/24jp7.
Billari, F. & Zagheni, E. (2017). Big Data and Population Processes: A Revolution? In: SIS 2017. Statistics and data science: new challenges, new generations (pp. 167–178). Florence: Firenze University Press. DOI: 10.36253/978–88–6453–521–0.
Bohme, M., Groger, A. & Stohr, T. (2019). Searching for a Better Life: Predicting International Migration with Online Search Keywords. Journal of Development Economics, 5, 1–32. DOI: 10.1016/j.jdeveco.2019.04.002.
Bohon, S. A. (2018). Demography in the Big Data Revolution: Changing the Culture to Forge New Frontiers. Population Research and Policy Review, 37(3), 323–341. DOI: 10.1007/s11113–018–9464–6.
Burch, T. (2018). Model-based demography. Essays on integrating data, technique and theory. Zürich: Springer, 200. DOI: 10.1007/978–3-319–654331.
Chayko, M. (2018). Superconnected. London: SAGE, 272.
Chudinovskikh, O. S. (2018). Big data and statistics on migration. Voprosy statistiki, 25(2), 48–56. (In Russ.)
Dmitrieva, T. E. & Chuprova, I. A. (2019). Possibilities and limitations of the modern statistical base for the analysis of socio-economic development of the Arctic zone of the Russia. In: Rol statistiki v sovremennom obshchestve i effektivnom upravlenii [The role of statistics in modern society and effective management] (pp. 91–98). Syktyvkar: Komistat. (In Russ.)
Dyatlov, S. A., Lobanov, O. S. & Zhou, W. (2018). The Management of Regional Information Space in the Conditions of Digital Economy. Ekonomika regiona [Economy of Region], 14(4), 1194–1206. DOI: 10.17059/2018–4-11. (In Russ.)
Fauzer, V. V. (2014). Demographic potential of the Russia’s northern regions as a factor and condition of economic development of the Arctic. Ekonomika regiona [Economy of Region], 4(40), 69–81. DOI: 10.17059/2014–4-5. (In Russ.)
Fedorov, A. M. & Datyev, I. O. (2019). Virtual population as a measure of digitalization in the regions. In: Teoriya i praktika sistemnoy dinamiki [Theory and practice of system dynamics] (pp. 159–164). Apatity: KNTs RAN publ. (In Russ.)
Ganichev, N. A. & Koshovets, O. B. (2019). Integrating Russia into the Global Project of Digital Transformation: Opportunities, Problems and Risks. Problemy prognozirovaniya [Studies on Russian Economic Development], 6(177), 49–59. DOI: 10.1134/S1075700719060030. (In Russ.)
Grimshaw, M. (2017). Digital society and capitalism. Palgrave Communications, 3(1), 1–3. DOI: 10.1057/s41599–017–0020–5.
Hughes, C., Zagheni, E., Abel, G., Wisniowski, A., Sorichetta, A., Weber, I. & Tatem, A. J. (2016). Inferring Migrations: Traditional Methods and New Approaches based on Mobile Phone, Social Media, and other Big Data. Luxembourg: Publications Office of the European Union, 41. DOI: 10.2767/61617.
Ilyin, V. I. (2014). The anatomy of social success in geographic space. Teleskop: zhurnal sotsiologicheskikh i marketingovykh issledovanii [Telescope: journal of sociological and marketing research], 6, 29–33. (In Russ.)
Katzenbach, C. & Bächle, T. C. (2019). Defining concepts of the digital society. Internet Policy Review, 8(4), 1–6. DOI: 10.14763/2019.4.1430.
Khazieva, N., Khaziev, A. & Klyushina, E. (2019). Digital Society: The Experience of the Philosophical Understanding of a Problem. Journal of History Culture and Art Research, 7(4), 347–353. DOI: 10.7596/taksad.v7i4.1856.
Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1(1), 1–12. DOI: 10.1177/2053951714528481.
Kotyrlo, E. (2019). Impact of Modern Information and Communication Tools on International Migration. International Migration, 58(4), 195–213. DOI: 10.1111/imig.12677.
Lytkina, T. S. & Smirnov, A. V. (2019). The Russian North in the Context of Global Neoliberal Politics: Overcoming Spatial Inequality or Expulsion? Mir Rossii [Universe of Russia], 3, 27–47. DOI: 10.17323/1811–038X-2019–28–3-27–47. (In Russ.)
Makhrova, A. G., Medvedev, A. A. & Nefedova T. G. (2016). Gardening and dacha communities of urban dwellers in the rural settlement system. Vestnik Moskovskogo universiteta. Seriya 5. Geografiya [Moscow University Bulletin. Series 5, Geography], 2, 64–74. (In Russ.)
Matzner, T. & Ochs, C. (2019). Privacy. Internet Policy Review, 8(4), 1–14. DOI: 10.14763/2019.4.1427.
Mkrtchyan, N. V. (2018). Regional Capitals and Their Suburbs in Russia: Net Migration Patterns. Izvestiya RAN. Seriya Geograficheskaya, 6, 26–38. DOI: 10.1134/S2587556618060110. (In Russ.)
Piché, V. (2013). Contemporary Migration Theories as Reflected in their Founding Texts. Population, 68, 141–164. DOI: 10.3917/popu.1301.0153.
Pyankova, A., Scherbakova, E. & Vasin, S. (2018). Population microcensuses in Russia: past, present and future. Demograficheskoe obozrenie [Demographic Review], 5(2), 61–102. (In Russ.)
Ruggles, S. (2014). Big Microdata for Population Research. Demography, 51(1), 287–297. DOI: 10.1007/s13524–013–0240–2.
Scott, A. & Storper, M. (2014). The Nature of Cities: The Scope and Limits of Urban Theory. International Journal of Urban and Regional Research, 39(1), 1–15. DOI: 10.1111/1468–2427.12134.
Weber, I. & State, B. (2017). Digital Demography. In: Proceeding WWW ‘17 Companion (pp. 935–939). Geneva: International WWW Conferences Steering Committee. DOI: 10.1145/3041021.3051104.
Zagheni, E. (2017). Data Science, Demography and Social Media Challenges and Opportunities. CSE 491: Data Science and Society, 66. Retrieved from: https://courses.cs.washington.edu/courses/cse491/17wi (Date of access: 01.06.2020).
Zamyatina, N. & Yashunsky, A. (2017). Migration cycles, social capital and networks. A new way to look at Arctic mobility. In: New Mobilities and Social Changes in Russia’s Arctic Regions (pp. 59–84). London, New York: Routledge.
Zamyatina, N. Yu. & Yashunsky, A. D. (2018). Virtual geography of virtual population. Monitoring obshchestvennogo mneniya: Ekonomicheskie i sotsialnye peremeny [Monitoring of Public Opinion: Economic and Social Changes], 1, 117–137. DOI: 10.14515/monitoring.2018.1.07. (In Russ.)
Zhuravleva, Е. Yu. (2015). Sociology in digital environment: towards digital social research. Sotsiologicheskie issledovaniya [Sociological Studies], 8, 25–33.
Zubarevich, N. V. (2017). Russia’s agglomerations development: trends, resources and governing. Obshchestvennye nauki i sovremennost [Social Sciences and Contemporary World], 6, 5–21. (In Russ.)
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Economy of Regions
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
