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ORIGINAL RESEARCH
Policy Topic Research on Chinese Environmental
Protection by an LDA Model of Text Mining
1
SILC Business School, Shanghai University, Shanghai 201800, China
2
School of Management, Shanghai University, Shanghai 200444, China
3
School of Business Administration, Shanghai University of International Business and Economics,
Shanghai 201620, China
Submission date: 2023-09-09
Final revision date: 2024-04-06
Acceptance date: 2024-05-29
Online publication date: 2024-10-07
Publication date: 2025-04-04
Pol. J. Environ. Stud. 2025;34(4):3933-3946
KEYWORDS
TOPICS
ABSTRACT
Environmental protection policies are an important manifestation of national development
and the maintenance of the community of human destiny, and China’s environmental protection
policies are of great significance to the environment, people’s livelihoods, and even the environmental
protection strategies of developing countries around the world. However, the evolution pattern of
China’s environmental protection policies at this stage is not clear. In this paper, the LDA model is used
to mine the text data of policy documents, trying to find the evolution law of China’s environmental
policy in different stages. The study found: (1) Through keyword statistics, environmental protection
policies focus on “ecological pollution”, “water pollution”, “enterprise production”, “supervision and
management” and other aspects. (2) The focus of environmental policies shifts over time from “mineral
resources” to “petroleum resources” to “ecological resources”. (3) In the future, “green agriculture”
and “water pollution penalties” will receive more policy support. The results of the above study
are expected to provide reference value for relevant scholars, enterprises, and governmental
environmental protection departments.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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| eISSN: | 2083-5906 |
| ISSN: | 1230-1485 |
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