Abstract
Discourse power is a tool to express social ideology, which controls the direction of public opinion in the whole society, and the competition for discourse power is the concrete manifestation of ideological struggle. With the development of artificial intelligence, the trend of information globalization is becoming more and more obvious. In the field of ideology, a hundred flowers bloom and a hundred schools of thought contend. At present, China’s socialist mainstream ideology is Sinicized Marxism - it is Mao Zedong Thought and socialist ideological system with Chinese characteristics guided by Marxism. However, with the influx and flood of Western discourse thoughts, our ideological education discourse has also been impacted to a certain extent. *** Therefore, this paper proposes an effective classification method for unbalanced data sets. The core idea of the classification of educational discourse unbalanced data sets based on mixed big data analysis is to provide a comprehensive solution for the classification of unbalanced data sets from two aspects: sample preprocessing and classifier improvement.
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General topic of Zhejiang Federation of Social Sciences “analysis and Reflection on the competency characteristics of excellent ideological and political teachers in Colleges and universities” (No.: 2022N124)).
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Teng, J. (2023). Classification Method of Educational Discourse Power Imbalance Data Set Based on Mixed Big Data Analysis. In: Jan, M.A., Khan, F. (eds) Application of Big Data, Blockchain, and Internet of Things for Education Informatization. BigIoT-EDU 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 466. Springer, Cham. https://doi.org/10.1007/978-3-031-23947-2_58
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DOI: https://doi.org/10.1007/978-3-031-23947-2_58
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