Poverty Measure Based on Hesitant Fuzzy Decision Algorithm under Social Network Media

This study aims to solve the problem that the traditional method of measuring the poverty level in rural and urban areas of China from a purely monetary perspective can’t comprehensively analyze and reflect the poverty. In this study, a multidimensional poverty measurement model with non-monetary indicators is proposed, the data of families and their members provided by the China Health and Nutrition Survey (CHNS) of a certain year’s health and nutrition survey in China are used for analysis, and a fuzzy set method is adopted to analyze the poverty situation in various regions of China. First, the fuzzy function set method is used to calculate the one-dimensional poverty index. On the basis of income, the multi-dimensional poverty fuzzy index is calculated from five dimensions, including education, health, assets, and living standard. The calculation results of the single-dimensional poverty and the multi-dimensional poverty are compared to further analyze the reasons of the family poverty of rural residents. Second, the poverty rate of each dimension in each region is calculated by referring to the appropriate measurement indexes of each dimension of the message passing interface (MPI) team. The results show that the concept of measuring poverty by the fuzzy set method is more sensitive to the overall distribution of population in the poverty dimension than the poverty line method. Compared with the poverty line method, the fuzzy set method can better consider the overall distribution of population in poverty dimension. Accordingly, China should strengthen the infrastructure construction in rural areas, increase the investment in education in rural areas, and improve the overall quality of the poor population.