The article concerns on the intensity and complexity of the changes in the field of Russian Citizens’ financial literacy in various regions. The special focus of the study is to identify the key infrastructural characteristics of digital financial literacy development among Russians. This kind of financial literacy considers a basic one in promoting and strengthening financial competence and culture. The methodology and methods of the research are based on a network approach and the general principles of social media predictive analytics. The cluster analysis conducted with R programming language and based on the Russian Citizens’ financial literacy open data presented six key regional clusters with certain features. This followed by the social media analysis with special software showed the regional characteristics of financial literacy information flows content and its infrastructure. The authors stress the strong potential of the most accessible and modern means of mass communication—popular social media—to empower people in terms of financial literacy. The study records tangible shifts in the structure of the financial literacy digital communities’ founders, determined by a decrease in the share of commercial structures and an increase in the representation of public and state institutions. The article highlights the recommendations for improving the social media infrastructure for the users’ financial culture empowerment.

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Russian Regional Features of Citizens’ Financial Literacy and Its Digital Infrastructure

  • Anna Dombrovskaya,
  • Alexandr Ognev,
  • Artur Azarov

摘要

The article concerns on the intensity and complexity of the changes in the field of Russian Citizens’ financial literacy in various regions. The special focus of the study is to identify the key infrastructural characteristics of digital financial literacy development among Russians. This kind of financial literacy considers a basic one in promoting and strengthening financial competence and culture. The methodology and methods of the research are based on a network approach and the general principles of social media predictive analytics. The cluster analysis conducted with R programming language and based on the Russian Citizens’ financial literacy open data presented six key regional clusters with certain features. This followed by the social media analysis with special software showed the regional characteristics of financial literacy information flows content and its infrastructure. The authors stress the strong potential of the most accessible and modern means of mass communication—popular social media—to empower people in terms of financial literacy. The study records tangible shifts in the structure of the financial literacy digital communities’ founders, determined by a decrease in the share of commercial structures and an increase in the representation of public and state institutions. The article highlights the recommendations for improving the social media infrastructure for the users’ financial culture empowerment.