Title |
Exploring stakeholders' opinions on circular economy in the construction sector: A natural language processing analysis of social media discourse |
ID_Doc |
4640 |
Authors |
Tleuken, A; Orel, D; Iskakova, A; Varol, HA; Karaca, F |
Title |
Exploring stakeholders' opinions on circular economy in the construction sector: A natural language processing analysis of social media discourse |
Year |
2024 |
Published |
Journal Of Industrial Ecology, 28, 4 |
DOI |
10.1111/jiec.13502 |
Abstract |
The construction industry has been criticized for its negative environmental impacts, leading industry experts to advocate for a shift toward a circular economy (CE) model. However, there is a lack of research on stakeholder opinions regarding that. This research paper examines stakeholders' perspectives on implementing CE principles in the construction industry by conducting artificial intelligence-powered natural language processing (NLP) through online sources. It answers three questions: What themes and concepts are associated with the CE in construction? How do opinions on the CE vary across different online platforms? And what factors shape positive attitudes toward the CE? The data obtained from various platforms showed that 57% of sentiments were positive, 28% were neutral, and 15% were negative. This research provides critical knowledge on the analysis of CE representation on social media in construction. Moreover, a webpage tool has been created that can assess any input opinion on the scale (positive, neutral, or negative) for further use (). This NLP-based research of social media discourse in the construction sector can directly influence policy decisions by offering real-time insights into public sentiment and preferences, shaping regulations that align with societal needs. It also provides industry professionals with data-driven guidance, enabling them to identify growth opportunities and innovation pathways within the CE, ultimately fostering a more sustainable and prosperous future. |
Author Keywords |
circular economy; construction sector; industrial ecology; sentiment analysis; sustainable buildings; topic modeling |
Index Keywords |
Index Keywords |
Document Type |
Other |
Open Access |
Open Access |
Source |
Science Citation Index Expanded (SCI-EXPANDED) |
EID |
WOS:001247901000001 |
WoS Category |
Green & Sustainable Science & Technology; Engineering, Environmental; Environmental Sciences |
Research Area |
Science & Technology - Other Topics; Engineering; Environmental Sciences & Ecology |
PDF |
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