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Abstract
In recent years, the imbalance of rural information supply and demand has seriously hindered the process of rural informatization. Rural information demand is a decisive factor in the relationship between rural information supply and demand. Therefore, research on the influencing factors of rural information demand has attracted much attention. The traditional rural information demand factor analysis does not consider the correlation between factors. The factors themselves carry a lot of repeated information, which seriously interferes with the objectivity of the analysis results. Proceeding from the complexity and diversity of influencing factors of rural information demand, based on the selected subjective and objective factors, based on the forward partial correlation analysis and post-ROC test, a probit discriminant model of influencing factors of rural information demand was constructed, and the relationship with Lingshou was determined. There are 24 factors that are significantly related to county rural information needs. The research results show that this method not only eliminates the factors that carry highly repetitive information and the correlation is not significant but also makes the results more reliable. At the same time, it also found that rural information supply is related to farmers’ information cognition ability, acceptance awareness, and acceptance ability. This study provides new methods and new ideas for solving related problems.
Highlights
With the rapid development of science and technology and the advent of the big data era, the construction of smart cities at home and abroad has made remarkable achievements
Evaluation of Influencing Factors of Rural Information Demand Based on Partial Correlation Analysis
The results show that all area under the curve (AUC) values are greater than 0.9, indicating that all factors are significantly related to rural information demand
Summary
With the rapid development of science and technology and the advent of the big data era, the construction of smart cities at home and abroad has made remarkable achievements. Guan Lili (2017) analyzed the information needs and constraints of farmers through questionnaires, especially the five characteristics of local farmers: the increasing variety of demand categories, the diversification of access methods, the depth of demand levels, the strong internal motivation of demand, and the strong ability of information research and judgment It provided experience in understanding the level of rural informatization and promoting the construction of information frameworks. From the perspective of information poverty alleviation, Li Gang and Qiao Haicheng (2017) proposed that the government should pay attention to information poverty alleviation through the construction of rural poverty-stricken area model and analysis of relevant data It has been found from the existing research that the information needs of farmers in China are increasingly strong and the demand structure is increasingly diversified, but the specialized information related to agricultural production development is still the most important component of farmers’ information consumption.
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