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Social acceptance dynamics and predictive scenario analysis of waste management policy

Author

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  • Stojcheva, Marija
  • Dedinec, Aleksandra
  • Dedinec, Aleksandar
  • Prodanova, Jana

Abstract

The objective of this study is to explore the intersection of public discourse and climate policy related to the waste management sector in the Republic of Macedonia. By integrating natural language processing (NLP) techniques, specifically sentiment analysis, topic modeling, and SHapley Additive exPlanations (SHAP), with scenario-based climate modeling aligned with IPCC guidelines, the research aims to assess the social acceptance and environmental potential of national waste strategies. The findings, from the analysis of X (formerly Twitter) data collected between October 2023 and April 2025, reveal a consistent predominance of negative sentiment, particularly toward opening new standardized landfills, with sharp sentiment peaks following local environmental events. The topic modeling results identify the landfill discourse as a dominant theme, with subtopics linked to public fear, mistrust and environmental health concerns. At the same time, the mitigation scenario projections indicate that full implementation of Macedonia's planned waste measures (mainly opening of new standardized landfills) could result in a 70 % reduction in GHG emissions by 2050, compared to a scenario with no measures. However, the widespread public disapproval toward key policy components, as evidenced in digital discourse, shows an inconsistency between technical feasibility and social acceptance. The study demonstrates the utility of a dual methodological lens to assist in a more responsive, inclusive, and sustainable policy design. It advocates for the institutionalization of digital discourse monitoring and transparent sentiment interpretation in public environmental governance, especially important in underrepresented regions like the Western Balkans.

Suggested Citation

  • Stojcheva, Marija & Dedinec, Aleksandra & Dedinec, Aleksandar & Prodanova, Jana, 2025. "Social acceptance dynamics and predictive scenario analysis of waste management policy," Chaos, Solitons & Fractals, Elsevier, vol. 200(P3).
    • Handle: RePEc:eee:chsofr:v:200:y:2025:i:p3:s0960077925011257
    DOI: 10.1016/j.chaos.2025.117112
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    References listed on IDEAS

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    1. Kiril Zelenkovski & Jana Prodanova & Ljupco Kocarev, 2024. "Exploring citizen perceptions and values for a responsible society," Social Science Quarterly, Southwestern Social Science Association, vol. 105(2), pages 296-310, March.
    2. Dilek Yildiz & Jo Munson & Agnese Vitali & Ramine Tinati & Jennifer Holland, 2017. "Using Twitter data for demographic research," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(46), pages 1477-1514.
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