Water Policy Evaluation Based on the Multi-Source Data-Driven Text Mining: A Case Study of the Strictest Water Resource Management Policy in China
文献类型：期刊论文
| 作者 | Cheng, Zhe3; Wang, Nina3; Zhao, Yuntong3; Cheng, Le1; Song, Tao2 |
| 刊名 | WATER
 |
| 出版日期 | 2022-11-01 |
| 卷号 | 14期号:22页码:18 |
| 关键词 | the strictest water resource management policy text mining multi-source data Baidu Index policy evaluation water governance |
| DOI | 10.3390/w14223694 |
| 通讯作者 | Song, Tao(songtao@igsnrr.ac.cn) |
| 英文摘要 | The strictest water resources management (SWRM) policy is a critical policy to address China's severe water shortage and pollution problems, and aims to promote sustainable water development and water governance. Based on data mining from multiple sources, including policy text from the strictest water resource management policy from 2011 to 2021, the reports of major media websites, and the Baidu Index, this study used the ROST-CM6 text-analysis tool to analyze the policy content, public opinion, and public perception of the strictest water resources management policy quantitatively and visually. The results found that the policy text and public-opinion are given high attention to the water resources assessment, water control management, and water resources protection, but the policy text focuses on the macro level, and pays more attention to national development and long-term planning. The public opinion belongs to the micro level and is more economic, and there is a certain degree of media bias. With notable regional disparities, the general public's opinion of the harshest water resource management policy has been rising every year. This research adds to the global body of knowledge on water governance, and serves as a guide for Chinese and other governments looking to improve their water resource management strategies. |
| WOS关键词 | GOVERNANCE ; STATE |
| 资助项目 | Major Program of Philosophy and Social Science Planning of Shaanxi Province[2021ZD2039] ; Major Program of Philosophy and Social Science of Chinese Ministry of Education[21JZD034] |
| WOS研究方向 | Environmental Sciences & Ecology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:000887893500001 |
| 出版者 | MDPI |
| 资助机构 | Major Program of Philosophy and Social Science Planning of Shaanxi Province ; Major Program of Philosophy and Social Science of Chinese Ministry of Education |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/187577]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Song, Tao |
| 作者单位 | 1.Zhejiang Univ, Guanghua Law Sch, Hangzhou 310058, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Xian Univ Architecture & Technol, Sch Publ Adm, Xian 710055, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cheng, Zhe,Wang, Nina,Zhao, Yuntong,et al. Water Policy Evaluation Based on the Multi-Source Data-Driven Text Mining: A Case Study of the Strictest Water Resource Management Policy in China[J]. WATER,2022,14(22):18. |
| APA | Cheng, Zhe,Wang, Nina,Zhao, Yuntong,Cheng, Le,&Song, Tao.(2022).Water Policy Evaluation Based on the Multi-Source Data-Driven Text Mining: A Case Study of the Strictest Water Resource Management Policy in China.WATER,14(22),18. |
| MLA | Cheng, Zhe,et al."Water Policy Evaluation Based on the Multi-Source Data-Driven Text Mining: A Case Study of the Strictest Water Resource Management Policy in China".WATER 14.22(2022):18. |
入库方式： OAI收割
来源：地理科学与资源研究所
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