The spatial organization of the national economy is changing. Network effects which are extremely difficult to identify in a multidimensional space are increasingly observed. In the digital economy, rapid identification of links with their subsequent consideration in strategic planning is possible based on applying algorithms for network analysis of big data arrays. Analysis of social networks originates in graph theory, however, it has only recently gained recognition as a research method. Development of algorithms for network analysis of large data arrays allows to build extremely large-scale networks of interaction of actors, for example, in social networks (Facebook, Twitter, Instagram, etc.). It is applicable to building diagnostic monitoring systems or identifying hidden dependences, which is well illustrated in the theory of “six handshakes”, Milgram's experiment, according to which any two people on Earth are separated by no more than five levels of common friends (and, accordingly, six levels of connections). Analysis of social networks can be used as a tool for content analysis of mass media and blogs to assess the popularity of certain ideas, concepts and images, as well as to identify the channels of their distribution. The study tested the possibility of applying network analysis and using the results for processing an array of large data obtained from social networks. We have created methodological developments for practical application of network analysis tools for the needs of strategic management, which have the potential to be used in integrated management systems. Successful testing of social network analysis tools for analyzing big data and developing a research algorithm available for replication in solving a wide range of analytical and search problems made it possible to identify sources of spatial consolidation and to establish that the method used makes it possible to obtain non-trivial results that track the dynamics of the problem field in the most mobile environment, on the Internet. It was revealed that there is a great potential in such solutions due to the fact that they make it possible to take into account the deployment of processes not only within the geographical space, but also to evaluate multidimensional links, defining sustainability and its boundaries based on the possibility of network reconstruction. The experimental study showed that using modern methods for analyzing arrays of big data and designing monitoring systems on them allows to further form the theoretical and methodological framework of a promising system for making strategic decisions and evaluating the performance of government based on the principles of reflection of final beneficiaries of social and economic policy.