Article
The effective path of ideological governance of university cyberspace in the context of big data
Authors
Abstract
This paper analyzes the characteristics of university cyberspace ideology in the context of big data and the causes of risk formation and designs the index system of university cyberspace ideology governance at three levels: micro level, meso level and macro level. The combination of hierarchical analysis and entropy method is used to determine the weight of each evaluation index and establish the evaluation model of governance performance based on gray correlation analysis. After calculating the weights of ideological security in college cyberspace are 0.58, 0.52, 0.55, 0.55 and 0.53, the evaluation result of the constructed college cyberspace ideology governance system is 0.28, which is good.
Keywords
Big data, Hierarchical analysis, Entropy method, Gray correlation method, Ideology, 97B20
Citation
Shang, F. (2023). The effective path of ideological governance of university cyberspace in the context of big data. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00895
F. Shang, “The effective path of ideological governance of university cyberspace in the context of big data,” Applied Mathematics and Nonlinear Sciences, vol. 8, no. 2, 2023, doi: 10.2478/amns.2023.2.00895.
Shang F. The effective path of ideological governance of university cyberspace in the context of big data. Applied Mathematics and Nonlinear Sciences. 2023;8(2). doi:10.2478/amns.2023.2.00895.
Shang, F. (2023), ‘The effective path of ideological governance of university cyberspace in the context of big data’, Applied Mathematics and Nonlinear Sciences, 8(2). Available at: https://doi.org/10.2478/amns.2023.2.00895.
Shang, Fengbiao. “The Effective Path of Ideological Governance of University Cyberspace in the Context of Big Data.” Applied Mathematics and Nonlinear Sciences, vol. 8, no. 2, 2023. https://doi.org/10.2478/amns.2023.2.00895.
Shang, Fengbiao. “The Effective Path of Ideological Governance of University Cyberspace in the Context of Big Data.” Applied Mathematics and Nonlinear Sciences 8, no. 2 (2023). https://doi.org/10.2478/amns.2023.2.00895.
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- DOI: 10.2478/amns.2023.2.00895
- Type: article
- Source: Applied Mathematics and Nonlinear Sciences
- Published: 2023-10-24
- OpenAlex ID: W4387922546
Published by: Engineering Journals


