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Exploring the motivations and obstacles of the public's garbage classification participation: evidence from Sina Weibo.

Wenqi WuMing Zhang
Published in: Journal of material cycles and waste management (2023)
China has been implementing garbage classification to improve resource recycling for many years. Since garbage classification is essentially a social activity, it needs the active participation of the public. However, the phenomenon of "high practice, low effect" is widespread in most cities. Therefore, this paper uses the data from Sina Weibo to analyze the reasons for the poor garbage classification effect. First, the key factors affecting residents' willingness to participate in garbage classification are identified based on the text-mining method. Further, this paper analyzes the reasons that promote or hinder the residents' intention of garbage classification. Finally, the resident's attitude towards garbage classification is explored by the score of the text's emotional orientation, and further the reasons for the positive and negative emotional orientation are analyzed, respectively. The main conclusions are as follows: (1) The proportion of residents holding negative sentiment towards garbage classification is as high as 55%. (2) Residents' positive emotions are mainly caused by the public's sense of environmental protection inspired by publicity and education, and the incentive measures taken by the government. (3) The main reasons for negative emotions are imperfect infrastructure and unreasonable garbage sorting arrangements.
Keyphrases
  • deep learning
  • machine learning
  • healthcare
  • mental health
  • quality improvement
  • primary care
  • physical activity
  • artificial intelligence
  • big data
  • risk assessment
  • electronic health record
  • smoking cessation