Author(s)

Hui Lv ¹, Cunjue Li ¹, Lingting Wang ¹

Affiliation(s)

¹ Chengdu International Studies University, Chengdu, Sichuan, 611844, China

Corresponding Author

Hui Lv

ABSTRACT

This study delves into the construction of an early warning system for social stability, thoroughly analyzing the comprehensive impact of political, economic, and cultural factors on societal stability. The article proposes a holistic early warning model based on feature selection, alert threshold setting, and factor analysis, aimed at accurately predicting and assessing the state of social stability. Through case studies of specific countries or regions, the article validates the practicality and effectiveness of the model, emphasizing the critical role of positive spiritual forces in maintaining social stability during economic challenges. Additionally, the article reviews the economic achievements in the early stages of China's socialist construction, underscoring the central position of Marxist belief in China's social stability and development, as well as historical experiences in the exploration of the socialist path.

KEYWORDS

Feature selection, alert threshold, spirituality, factor analysis

CITE THIS PAPER

Hui Lv, Cunjue Li, Lingting Wang, Social Stability Early Warning Study. Social Security and Administration Management (2024) Vol. 5: 72-78. DOI: http://dx.doi.org/10.23977/socsam.2024.050210.

REFERENCES

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[2] Wang Siyu, Design and Implementation of Social Stability Index Evaluation Information System [D]. Northeast University, 2015 
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[4] Liu Huanshen, Research on Lenin's Thought of Russian Development Path before the October Revolution [D]. Shandong Normal University, 2021. DOI: 10.27280/d.cnki. gods.2021.000023
[5] Guo Jinyu; Zhang Zhongbin; Sun Qingyun. "Advances in the Stagger Analysis Methodology for Structural Integrity Assessment." Structural Engineering and Mechanics, vol. 65, no. 2, Feb. 2017, pp. 213-220. DOI: 10.18282/sem. v0i65.2345
[6] Wang, Binhui; Li, Xiongying. "A Comparative Investigation into the Robustness of Factor Analysis Techniques in Financial Modeling." Journal of Quantitative & Technical Economics, vol. 34, no. 4, Apr. 2017, pp. 78-92. DOI: 10.27110/jqte.2017.v34i4.0102

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