Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation

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, a...

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Main Authors: Junhao Song, Yingfang Yuan, Kaiwen Chang, Bing Xu, Jin Xuan, Wei Pang
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Energy and AI
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666546824000995
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author Junhao Song
Yingfang Yuan
Kaiwen Chang
Bing Xu
Jin Xuan
Wei Pang
author_facet Junhao Song
Yingfang Yuan
Kaiwen Chang
Bing Xu
Jin Xuan
Wei Pang
author_sort Junhao Song
collection DOAJ
description 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.
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issn 2666-5468
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publishDate 2024-12-01
publisher Elsevier
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series Energy and AI
spelling doaj-art-82db3b807aa248b8a016b9f95c6699d22025-08-20T02:49:00ZengElsevierEnergy and AI2666-54682024-12-011810043310.1016/j.egyai.2024.100433Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisationJunhao Song0Yingfang Yuan1Kaiwen Chang2Bing Xu3Jin Xuan4Wei Pang5School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, United Kingdom; Faculty of Engineering, Imperial College London, London, United KingdomSchool of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, United KingdomSchool of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, ChinaEdinburgh Business School, Heriot-Watt University, Edinburgh, United KingdomFaculty of Engineering and Physical Sciences, University of Surrey, Surrey, United KingdomSchool of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, United Kingdom; Corresponding author.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.http://www.sciencedirect.com/science/article/pii/S2666546824000995Circular economyPulic attentionTopic modellingMachine learningHyperparameter optimisation
spellingShingle Junhao Song
Yingfang Yuan
Kaiwen Chang
Bing Xu
Jin Xuan
Wei Pang
Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation
Energy and AI
Circular economy
Pulic attention
Topic modelling
Machine learning
Hyperparameter optimisation
title Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation
title_full Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation
title_fullStr Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation
title_full_unstemmed Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation
title_short Exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation
title_sort exploring public attention in the circular economy through topic modelling with twin hyperparameter optimisation
topic Circular economy
Pulic attention
Topic modelling
Machine learning
Hyperparameter optimisation
url http://www.sciencedirect.com/science/article/pii/S2666546824000995
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