Research on the intelligent path of college students’ network ideological and political education based on big data mining technology

Abstract

Abstract As big data mining technology is known to directly change the development direction and internal management, and the behaviour of college students’ political wisdom network has also changed significantly, hence the application and analysis of data mining technology becomes indispensable. Bidirectional gated cyclic cell network can solve the gradient disappearance or gradient explosion existing in traditional models, but can also make up for the deficiency of extracting the contextual semantic information of long text effectively. Using the combination of big data-based mining technology and college students’ network ideology and politics, this paper designed a set of BiGRU_Attention framework based on college students’ network ideological wisdom framework and adopted big data mining technology to collect data. First, according to the Internet technology and information collection, design a complete set of college students’ ideological wisdom framework. Then, the GRU structure, BiGRU framework and Attention mechanism combined with BiGRU_Attention model are introduced. Meanwhile, Word2Vec is used to train the Chinese word vector. Finally, the BiGRU_Attention proposed in this paper is compared with several models. Experimental results show that the BiGRU_Attention proposed in this paper has a better accuracy of 96.32% over other models. The experimental results also show that the framework of ideological and political intelligence proposed in this paper can be applied to the campus environment of college students.