Attitude of Chinese public towards municipal solid waste sorting policy: A text mining study

被引:99
作者
Wu, Zezhou [1 ,2 ]
Zhang, Yan [1 ]
Chen, Qiaohui [3 ]
Wang, Hao [4 ]
机构
[1] Shenzhen Univ, Sino Australia Joint Res Ctr BIM & Smart Construc, Shenzhen, Peoples R China
[2] Shenzhen Univ, Key Lab Coastal Urban Resilient Infrastruct, Shenzhen, Peoples R China
[3] Hong Kong Polytech Univ, Dept Bldg & Real Estate, Hong Kong, Peoples R China
[4] Cent Univ Finance & Econ, Sch Management Sci & Engn, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
MSW sorting policy; Public attitude; Text mining; LDA topic model; China; SOURCE SEPARATION; HOUSEHOLD WASTE; ORGANIC WASTE; MANAGEMENT; BEHAVIOR; MODEL; CLASSIFICATION; CONSTRUCTION; MECHANISM; SENTIMENT;
D O I
10.1016/j.scitotenv.2020.142674
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the acceleration of urban development, the amount of municipal solid waste (MSW) has increased dramatically. In order to recycle MSW more efficiently, a compulsory policy of sorting MSW has been enacted in China. According to the existing literature, attitude is an important factor affecting public's MSW sorting behavior. To explore the Chinese residents' emotional tendency towards the MSW sorting policy, this study analyzed the data of Sina Weibo users and their comments on related popular posts. Meanwhile, text mining technology was employed to analyze the collected data. Results showed that although a large proportion of the Chinese public has a positive attitude towards the MSW sorting policy, the proportion of people with negative emotions reached nearly half. In addition, it was found that the Chinese people in different regions pay different attentions to the MSW sorting policy. Results further revealed that the main reasons for the public's negative emotions were fines, MSW sorting rules, fees, timing of throwing waste, and irregular recycling procedures. By providing the public sentiment analysis of MSW sorting, this study can serve as a policy guide for practitioners and policymakers to link current research areas into social development. (C) 2020 Elsevier B.V. All rights reserved.
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页数:10
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