分类
拆毁
斯科普斯
产品(数学)
计算机科学
多样性(控制论)
集合(抽象数据类型)
内容分析
社会化媒体
比例(比率)
骨料(复合)
数据科学
工程类
土木工程
万维网
数学
地理
社会科学
几何学
地图学
梅德林
材料科学
人工智能
社会学
法学
政治学
复合材料
程序设计语言
作者
Deirdre Frances Mair,Samad M. E. Sepasgozar,Faham Tahmasebinia,Sara Shirowzhan
出处
期刊:Journal of Architectural Engineering
[American Society of Civil Engineers]
日期:2023-09-01
卷期号:29 (3)
标识
DOI:10.1061/jaeied.aeeng-1218
摘要
This study developed novel metrics and utilized content analysis in terms of keywords selected, scholarly publications, and social media posts to identify trends and industry involvement. A data set of publications was created based on collected materials from Scopus and social media and analyzed using statistical tests, rigorous content analysis, and network analysis. The data set was used to develop a framework for assessing the maturity of research topics and a classification system for labeling publications. The framework includes some indicators, such as total publications and a variety of applications, which are assessed based on a scale of 4. The classification system suggests four components: (1) product, (2) construction and demolition waste, (3) additives, and (4) experiments to be considered by authors. The framework and the categorization system may assist academics and practitioners in predicting topic trends and offer a set of indicators for conducting systematic reviews to identify gaps in the literature. Also, total publications as one of the framework indicators reveals that 46% of Canadian publications and 20.7% of US publications exhibited industry involvement compared with 15% of Australian publications and 15% of UK publications. The analysis shows that the top-occurring keyword in the data set is recycled asphalt pavement, which is linked to 22.2% of the data set, followed by recycled concrete and recycled aggregate concrete appearing in 12%. Aside from keywords related to materials, two of the most commonly occurring techniques in the data set of keywords are building information modeling and life cycle assessment, which still need further investigation along with GIS for waste minimization.
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