The circular economy through the prism of machine learning and the YouTube video media platform

被引:3
作者
Tsironis, Georgios [1 ]
Daglis, Theodoros [2 ]
Tsagarakis, Konstantinos P. [2 ]
机构
[1] Democritus Univ, Dept Environm Engn, Xanthi 67100, Greece
[2] Tech Univ Crete, Sch Prod Engn & Management, Khania 73100, Greece
关键词
Circular economy; Latent Dirichlet allocation; YouTube; Machine learning; Social media; SOCIAL MEDIA;
D O I
10.1016/j.jenvman.2024.121977
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The transition to a Circular Economy (CE) is rapidly gaining ground across countries and industries. It is the means of achieving more sustainable development by adopting innovative environmentally friendly strategies and saving primary resources. There are several studies indicating the increasing public and corporate interest in the CE but still remain limited in terms of the multitude and utilization of social media data. This work aims to shed light on the most common topics discussed on the YouTube platform, related to the CE. For this reason, we selected 17 videos including the term "Circular Economy" since these have been the most relevant with a sufficient number of comments and views. The model identified two main topics referring to "Sustainable industry and environmental responsibility" and "Circular Economy and resource management" which is a strong indicator of the people's interest in the utilization of resources alongside industrial and corporate activities. The two-topic configuration presented the highest coherence score; however, five and ten-topic configurations have been deployed since there was no extreme differentiation in the model's performance, which could provide more detailed insights. This work's innovation lies in utilizing Machine Learning techniques and social media data to unravel CE's debates.
引用
收藏
页数:12
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