Abstract
To advance the circular economy (CE), it is crucial to gain insights into the evolution of public attention, cognitive pathways related to circular products, and key public concerns. To achieve these objectives, we collected data from diverse platforms, including Twitter, Reddit, and The Guardian, and utilised three topic models to analyse the data. Given the performance of topic modelling may vary depending on hyperparameter settings, we proposed a novel framework that integrates twin (single- and multi-objective) hyperparameter optimisation for CE analysis. Systematic experiments were conducted to determine appropriate hyperparameters under different constraints, providing valuable insights into the correlations between CE and public attention. Our findings reveal that economic implications of sustainability and circular practices, particularly around recyclable materials and environmentally sustainable technologies, remain a significant public concern. Topics related to sustainable development and environmental protection technologies are particularly prominent on The Guardian, while Twitter discussions are comparatively sparse. These insights highlight the importance of targeted education programmes, business incentives adopt CE practices, and stringent waste management policies alongside improved recycling processes.
| Original language | English |
|---|---|
| Article number | 100433 |
| Journal | Energy and AI |
| Volume | 18 |
| Early online date | 22 Oct 2024 |
| DOIs | |
| Publication status | Published - Dec 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
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SDG 12 Responsible Consumption and Production
Keywords
- Circular economy
- Hyperparameter optimisation
- Machine learning
- Pulic attention
- Topic modelling
ASJC Scopus subject areas
- General Energy
- Artificial Intelligence
- Engineering (miscellaneous)
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Dive into the research topics of 'Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation'. Together they form a unique fingerprint.Datasets
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Public Attention Text Dataset on Circular Economy for Topic Modelling
Song, J. (Creator), Yuan, Y. (Creator), Chang, K. (Creator), Xu, B. (Creator), Xuan, J. (Creator) & Pang, W. (Creator), Heriot-Watt University, 25 Jun 2025
DOI: 10.17861/85bf3f9d-dc42-4b5c-8e29-47ddd0f0f687
Dataset
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