Measuring the socio-economic development of regions: from classical approaches to digital social scoring

The subject of the research covers the theoretical and practical foundations of assessing the socio-economic well-being of regions using traditional and innovative approaches. The analysis focuses on identifying the limitations of classical indicators, such as gross regional product, income levels, and demographic characteristics, which do not fully reflect the subjective perception of the quality of life by the population. The study examines international indices (Social Progress Index, Happy Planet Index, World Happiness Report), as well as Russian practices of comprehensive assessment (ratings by RIA Novosti, Expert RA), allowing the identification of their strengths and weaknesses. Additional emphasis is placed on the potential to use digital data and natural language processing methods, including sentiment analysis of texts, to integrate subjective evaluations and public sentiments into the monitoring system. The methodology of the research is based on applying critical analysis methods and comparative reviews of the scientific literature, generalizing the concepts of "happiness economics" and integral indices, and employing an interdisciplinary approach that allows for comparing traditional indicators and digital methods of assessing well-being. The scientific novelty lies in the systematization of theoretical schools and indices aimed at measuring well-being, justifying the need for integrating subjective digital indicators into traditional monitoring models of socio-economic development of regions. The novelty is also manifested in emphasizing the application of computational social science methods, including automated text analysis, as a promising direction to enhance the sensitivity and timeliness of monitoring. The proposed approach expands existing practices, allowing not only to capture objective indicators but also to consider the dynamics of public sentiments, which changes the system of assessing well-being towards greater completeness and comprehensiveness. Conclusions: classical indicators (GRP, income) reflect the standard of living in a limited manner, while international and Russian ratings, despite their complexity, remain static and lag behind in time. The use of digital indicators for social scoring enables the formation of more timely and representative monitoring. They combine economic, sociological, and digital approaches, providing more accurate diagnostics of regional development and creating a tool to support strategic decisions in regional policy.

socio-economic development, regional well-being, happiness index, sustainable development, digital footprints, sentiment analysis, social scoring, regional economics, big data, public sentiment