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International Journal of Big Data Intelligent Technology, 2024, 5(1); doi: 10.38007/IJBDIT.2024.050103.

Application of WeChat Public Platform in the Construction of College Students' Campus Culture under the Background of Big Data


Xingwu Wang, Feng Yang

Corresponding Author:
Feng Yang

School of Physical Education, Hunan University of Arts and Science, Changde 415000, Hunan, China


For a long time, propaganda and ideological work has always been the key content in the field of ideology. As an important position for propaganda and ideological work, colleges and universities are more responsible for placing propaganda and ideological work in an important position. The purpose of this paper is to study the application of WeChat public platform in the construction of college students' campus culture based on the background of big data. The platform architecture is analyzed for the WeChat public platform of M University, and the main functional modules in the platform are analyzed in detail. The mobile terminal adopts J2EE technology, and the background is developed in Java. In the interaction, the representation of data information is realized through JSON. Starting from the basic situation of students in M University using the school's official WeChat public platform, to understand how and how the communication of the university's micro-platform has affected the campus cultural identity, explore the reasons, and explore how to improve on the existing basis to achieve more good communication effect. The content of M University's official Weibo and WeChat public platform texts are analyzed, and the characteristics and laws of transmission are summarized, so as to try to analyze how the official micro-platform of M University affects the campus cultural identity.


Big Data Background, WeChat Public Platform, College Campus, Cultural Construction

Cite This Paper

Xingwu Wang, Feng Yang. Application of WeChat Public Platform in the Construction of College Students' Campus Culture under the Background of Big Data. International Journal of Big Data Intelligent Technology (2024), Vol. 5, Issue 1: 15-22. https://doi.org/10.38007/IJBDIT.2024.050103.


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