In the digital age, neighborhood communication has shifted to the online space, altering the traditional nature of interactions. This raises questions about the applicability of traditional knowledge about neighborhoods to their online counterparts. This study examines the impact of social capital within online neighborhood communities on political communication among their members. To do so, we analyzed the digital footprints of online neighborhood communities in the city of Volgograd, including all districts and types of buildings. Using machine learning techniques for natural language processing and network analysis, we examined over 79,000 posts over a 17-year period to evaluate the impact of both structural and relational dimensions of social capital. The results indicated that the characteristics of social capital in online communities influence political communication in a similar way to traditional interactions. A sense of community, high density, and the clustering of the network, as well as the presence of key intermediary nodes, contribute to discussions about political topics. This suggests that digital platforms can replicate the social mechanisms found in offline environments, and that previously accumulated knowledge about the impact of neighborhoods on political participation can be applied in a digital context.

The article contains the results of the study of political mobilization of protest communities in the social network VK. The set of such communities (network cluster) was mapped in winter — spring 2021. The state of the same cluster was studied in late 2023 — early 2024. The comparison of the two sub-periods allowed us to propose an answer to the key research question: how the change in the political situation affected the activity of protest groups. To calculate the level of mobilization, a new indicator was imported from the theory of self-organized criticality, which is a natural science concept. This indicator allows us to identify (through the analysis of dynamic series of network activity) communities that are characterized by high user involvement and are able to influence the behavior of their members. The author showed that the cluster was partially mobilized in 2021, but shrunk by more than two-thirds by 2024. Few communities show high levels of mobilization during the second sub-period. The cluster, however, is likely to recover as new nodes and links emerge.

The article is devoted to defining the digital revolution in the development of communication technologies as a key factor in the evolution of state–confessional relations. It demonstrates the risks associated with the popularization in social media of a simplified interpretation of the principle of secularism and the spread of critical, distorted, and biased media representations of the socio-political interaction between the state and religious denominations. A negative attitude toward the role of religion in the socio-political sphere may be used by pro-Western activists as a resource for opposition mobilization. Technologies of protest politicization of state–confessional partnership are analyzed using specific cases such as the conflicts surrounding the transfer of St. Isaac’s Cathedral in Saint Petersburg to the jurisdiction of the Russian Orthodox Church and the construction of a church in Yekaterinburg in a public square area. The application of post-secular theory and the concept of the “smart mob” makes it possible to conclude that a new technology of informational influence has emerged — religious labeling. The development of the information infrastructure of the Russian Orthodox Church, including the use of social networks, bloggers, digital platforms, and Telegram channels, makes it possible to ensure the dissemination of positive media representations of state–confessional interaction and social partnership. The article provides examples of successful practices in the development of charitable platforms, the implementation of educational programs, and the promotion of Russia’s traditional spiritual and moral values.

The article is devoted to the consideration of deplatforming as a new method of digital control and digital cancellation culture. In the context of widespread digitalization of government policy and large corporations are faced with the need to adapt to unusual models of political and managerial decision-making, in which digital platforms and neuroalgorithmic tools for content moderation play a significant role. The digital power of media corporations is implicitly linked to network algorithms, which universally implement adaptive rules that are mandatory for all participants in network interaction. These rules are often restrictive. In this regard, from the point of view of practical policy, the issue of the application of digital deplatforming is important. The author provides examples of digital deplatforming, which show the ambiguity of using this technology. The article reveals the fundamental issues of deplatforming: who is deplatforming? what is being deplatformed? why are they being deblatformed? how exactly do they de-platform? is replatforming possible? As a result of the research, the author identifies the dominant.

The concept of ‘consent engineering’ developed by social psychologist and technologist Edward Bernays in the first half of the 20th century, has become a cornerstone of modern public relations, political communication, and social governance. This article deconstructs the paradox of the Bernays’s model: how the desire for rational governance of people gave rise to manipulative technologies of mass influence on society as a whole. This article analyzes how Bernays’s classic ideas anticipated the era of modern post-truth and digital algorithms, transforming the understanding of public policy democracy. The authors examine the emergence of a new version of consent engineering in the era of algorithmic power and other digital circuits This article also analyzes the transformation of consent-building methods — from classic mass communication tools to algorithmic platforms using big data and artificial intelligence.