The Use of Social Media to Study the Features of Commuting in Russian Million-Plus Cities
DOI:
https://doi.org/10.17059/ekon.reg.2023-4-13Keywords:
commuting, social networks, million-plus cities, spatial development, population mobility, delimitation of agglomeration boundaries, labour market, big dataAbstract
Commuting as a feature of agglomeration processes, and its examination in the context of spatial development becomes relevant. Simultaneously, considering the limited availability of official municipal statistics, new data sources for such a research are necessary. The study aims to explore the possibility of using open data from VKontakte social network to identify and analyse commuting in 14 Russian million-plus cities (agglomeration centres) and 97 settlements (satellites). It is hypothesised that the outflow of labour from a million-plus city is comparable to the influx of labour from satellite cities to replace this outflow. The methods of social media analytics, correlation and comparative analysis, cartographic techniques were applied. The Federal State Statistics Service data and anonymous VKontakte user data obtained in the spring of 2023 were analysed using the author’s computer programme. The analysis showed that the higher the share of citizens of million-plus cities working outside their city, the lower the average share of residents of satellite cities working in agglomeration centres. A negative correlation between the distance from a city of residence to an agglomeration centre and the share of the commuting population was revealed. This finding confirms the presence of a gravity criterion used to determine the boundaries of urban agglomerations according to gravity models. Additionally, a positive correlation between the labour market tension and the share of residents of satellite cities working in agglomeration centres was noted. It was concluded that social media data provides new opportunities for identifying and assessing commuting flows. The research results can be used to further study commuting features, intensity and directions in order to take them into account when creating spatial development strategies.
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