Construction and Implementation of Marxist Learning Platform in New Media Environment

• Published in: Journal of environmental and public health Vol. 2022; no. 1; p. 1231601
• Main Authors: Deng, Lina, Zhang, Fuguo, Yang, Bo
• Format: Journal Article
• Language: English
• Published: New York Hindawi 2022; John Wiley & Sons, Inc; Hindawi Limited
• Subjects: Algorithms; Audiences; Big Data; Clustering; College campuses; Communication; Construction; Data mining; Distance learning; Education; Globalization; Ideology; Innovations; Learning; Machine learning; Marxism; Materialism; Philosophy, Marxist; Propaganda; Socialism; Society; Technology application; Values; China
• ISSN: 1687-9805; 1687-9813
• DOI: 10.1155/2022/1231601

Popularizing contemporary Chinese Marxism is urgently needed in order to support the ongoing development of socialism with Chinese characteristics as well as the inherent necessity of Marxism. This essay views the popularization of Marxism as a turning point in the new media environment. It examines the necessity and reality of this popularization in the new media era, considers the new development needs of the popularization of Marxism in propaganda, and further unearths the original construction concepts of the popularization of the Marxism propaganda network. In parallel, a Marxist learning platform is built using data mining technology. Studies reveal that this algorithm has a high clustering accuracy and a recall rate that is about 6% higher than DECluster’s. Additionally, this algorithm takes less time to execute under the same scale transaction set. This demonstrates the superior performance of this algorithm. The user’s learning record and learning interests can be formed into an intuitive law using the algorithm presented in this study, which can be used to analyze and calculate the user’s learning content related to Marxism. This law can then be used to assist the user in creating a customized learning plan for Marxism.