Nedoseka E.V., Nenko A.E. (2025) Mapping Community Structure at the City Scale Using Social Media Data. Monitoring of Public Opinion: Economic and Social Changes. No. 5. P. 223–250. https: ... Nedoseka E.V., Nenko A.E. (2025) Mapping Community Structure at the City Scale Using Social Media Data. Monitoring of Public Opinion: Economic and Social Changes. No. 5. P. 223–250. https://www.doi.org/10.14515/monitoring.2025.5.3034. (In Russ.)ISSN 2219-5467DOI 10.14515/monitoring.2025.5.3034Posted on site: 14.11.25Текст статьи на сайте журнала URL: https://www.monitoringjournal.ru/index.php/monitoring/article/view/3034 (дата обращения 14.11.2025)AbstractUrban projects, at least in their fundamental value principles, imply the involvement of citizens and their self-organized groups in the discussion and adoption of democratic, fair and inclusive decisions regarding urban changes. Understanding the interests and values that unite communities of citizens, the urban spaces with which they are connected, the local expertise they accumulate, as well as potential conflicts between them and other stakeholders of urban processes, is the goal of mapping urban communities within urban projects. However, within the framework of applied projects, financial, time and human resources for comprehensive field research are limited. In this case, the solution may be to identify those communities that are united through digital social networks and demonstrate agency in the digital space of the city. In this article, we combine the results of international sociological research and the practice of urban studies, which have an interdisciplinary nature and are conditioned by the pragmatics of specific changes in the urban environment. We describe an approach to mapping urban communities based on open data from city social networks, which includes searching, structuring data and typology of urban communities, as well as a description of indicators of their activity and forms of their activity. This approach was developed by us in the course of applied urban projects and is data-driven (that is, it relies on data that was collected and processed in the process of applied research). The proposed typology of digital urban communities is open and can be modified in view of the specific tasks of new projects.