School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Ave 639798, Singapore.
Department of Statistics and Data Science, National University of Singapore, Science Drive 2 117546, Singapore.
Waste Manag. 2024 Jun 15;182:113-123. doi: 10.1016/j.wasman.2024.04.028. Epub 2024 Apr 21.
The research pertaining to solid waste is undergoing extensive advancement, thereby necessitating a consolidation and analysis of its research trajectories. The existing biblio-studies on solid waste research (SWR) lack thorough analyses of the factors influencing its trends. This article presents an innovative categorization framework that categorizes publications from six SWR journals utilizing Source Latent Dirichlet Allocation. First analyse changes in publication numbers across main categories, subcategories, journals, and regions, providing a macro-level study of SWR. Temporal analysis of keywords supplements a micro-level study of SWR, which highlights that emerging technologies with low Technology Readiness Level receive significant attention, while studies on widespread technologies are diminishing. Additionally, this study demonstrates the substantial influence of socioeconomic factors and previous SWR publications on current and future SWR trends. Finally, the article confirms the impact of global events on SWR trends by examining the structural breakpoints of SWR and their correlation with global events.
固体废物研究正在取得广泛进展,因此需要对其研究轨迹进行整合和分析。现有的固体废物研究(SWR)文献研究缺乏对影响其趋势的因素的深入分析。本文提出了一种创新的分类框架,利用来源潜在狄利克雷分配(Source Latent Dirichlet Allocation)对来自六个 SWR 期刊的出版物进行分类。首先,分析主要类别、子类别、期刊和地区的出版物数量变化,对 SWR 进行宏观研究。关键词的时间分析补充了 SWR 的微观研究,突出了具有低技术准备水平的新兴技术受到了极大关注,而对广泛应用技术的研究却在减少。此外,本研究还表明,社会经济因素和以前的 SWR 出版物对当前和未来 SWR 趋势有重大影响。最后,通过检验 SWR 的结构断点及其与全球事件的相关性,本文证实了全球事件对 SWR 趋势的影响。