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Revealing public attitudes toward ‘substituting plastic with bamboo’ in China: Sentiment and topic analyses using social media data

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Listed:
  • Ji, Jingsong
  • Xu, Xiaoxiao
  • Tam, Vivian W.Y.
  • Zhang, Yangzi

Abstract

Public attitudes play a critical role in the successful implementation of national policies. However, there is a scarcity of systematic research presenting the Chinese public's sentiments regarding the “substituting plastic with bamboo” policy. With the increasing use of social media platforms for expressing views on policies, this research employs web crawler technology to collect public data from TikTok, Bilibili, and Sina Weibo, and uses statistical analysis and text mining techniques for investigation. The findings indicate that public discourse is strongly influenced by the announcement of related national policies. Commonly identified keywords in the analysis include “plastic bag,” “cut,” “chopsticks,” “moldy,” “single use,” “garbage,” and “buy.” Sentiment analysis reveals that neutral sentiments account for more than one-third of all comments, with positive sentiments marginally outnumbering the negative ones. The negative sentiments predominantly express concerns about the quality and cost of bamboo wares, environmental repercussions, and policy implementation challenges. Using Latent Dirichlet Allocation topic analysis, six key topics were identified based on Coherence and Jensen-Shannon Divergence metrics: economic environmental impact, the feasibility of substitution, impact on daily life, utilization of bamboo wares, production challenges, and policy implications. This research concludes with several policy recommendations. The insights gained from this research can assist the Chinese government and bamboo ware manufacturers in understanding market dynamics and in crafting more effective policies and strategies.

Suggested Citation

  • Ji, Jingsong & Xu, Xiaoxiao & Tam, Vivian W.Y. & Zhang, Yangzi, 2025. "Revealing public attitudes toward ‘substituting plastic with bamboo’ in China: Sentiment and topic analyses using social media data," Forest Policy and Economics, Elsevier, vol. 176(C).
  • Handle: RePEc:eee:forpol:v:176:y:2025:i:c:s1389934125000875
    DOI: 10.1016/j.forpol.2025.103508
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