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The effectiveness of the above methods for determining consumer sentiment at the present stage of society’s development is declining. Traditional surveys and questionnaires are gradually moving to the Internet. Modern users often try to avoid this form of opinion assessment, which results from the population’s distrust due to the growth of Internet fraud. The same applies to traditional contact methods for questionnaires. At the same time, conducting research based on statistical data may not always reflect the actual state of the issue under study due to the influence of numerous factors. Among these are the inability to fully cover subjects’ economic activities, their underestimation of the results of their activities, and the growth of the shadow economy. In addition, a significant factor involves the retrospective nature of statistical data. According to some indicators, collecting and processing information takes a long time—up to six months. Thus, a study based on statistical data allows us to obtain a result reflecting consumer sentiment only over past periods. At the same time, to develop effective management decisions in various spheres of society’s economic and social life, it is necessary to have a current idea of this indicator.
Notably, in Russian practice, the use of big data processing programs to determine the population’s opinion and assess the degree of satisfaction with the economic situation and confidence in state policy in this area has been poorly studied. However, such studies are actively conducted all over the world. Many foreign scientists have studied the possibilities, features, and effectiveness of the application of big data.
Thus, at the moment, no methods exist for using text mining technologies in Russia to determine the population’s satisfaction. The possibilities of adapting technologies to work with the Russian text have not been studied, which does not allow for the development of their application in the socio-economic sphere of the country.
The purpose of this work is to assess the population of the Russian Federation’s satisfaction with their incomes based on the analysis of social network data using text mining tools. Studying this issue will allow us to get an idea of the features of the use of text mining technologies in the processing of texts from Russian-language sources, as well as to develop a methodology for building on this basis the wage satisfaction index as one of the components of the composite index of economic sentiment.