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Tweeting Circular Economy: Unveiling Current Discourse Through Natural Language Processing

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  • Muhammad Rifqi Maarif
  • Arif Budy Pratama
  • Michael Hutahaean
  • Arif Rahman Saleh
  • Norma Latif Fitriyani
  • Muhammad Syafrudin

Abstract

In recent years, the circular economy (CE) has emerged as a critical strategy for sustainable development, addressing environmental challenges, resource efficiency, and waste reduction. Although the advantages of CE over traditional linear economic models are well‐documented, less attention has been given to understanding how CE is perceived and discussed in public forums such as social media. This paper aims to fill that gap by analyzing Twitter conversations related to CE from 2012 to 2022, using advanced Natural Language Processing (NLP) techniques. A total of 389,575 tweets were collected and processed to uncover the main themes, trends, and influential entities in the global CE discourse. The analysis shows that waste management, recycling, and resource efficiency are the most prevalent topics, reflecting the public's concern for practical CE applications. Additionally, technological advancements such as blockchain and IoT are emerging as significant drivers of CE innovation. Countries like the United Kingdom, China, and India, along with key organizations like the European Commission and the Ellen MacArthur Foundation, are central to the global CE narrative. These findings provide critical insights for policymakers, corporations, and researchers, highlighting areas of public interest and potential collaboration to advance CE initiatives. By aligning strategies with social media discourse, stakeholders can promote more effective, widespread adoption of CE principles.

Suggested Citation

  • Muhammad Rifqi Maarif & Arif Budy Pratama & Michael Hutahaean & Arif Rahman Saleh & Norma Latif Fitriyani & Muhammad Syafrudin, 2025. "Tweeting Circular Economy: Unveiling Current Discourse Through Natural Language Processing," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(3), pages 3888-3905, June.
    • Handle: RePEc:wly:sustdv:v:33:y:2025:i:3:p:3888-3905
    DOI: 10.1002/sd.3323
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    References listed on IDEAS

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