Os estudos de colaboração científica têm ganhado expressividade nas mais diferentes áreas do conhecimento, pois demonstram ser um importante componente para a sedimentação dos campos de pesquisa. ...Considerando a importância do fenômeno colaborativo para a área de Secretariado Executivo, esse trabalho objetivou: a) analisar a existência de uma rede de colaboração científica entre os pesquisadores associados à ABPSEC, no período de 2016 a 2020; b) compreender o comportamento dos pesquisadores e as características e propriedades dessa rede. Conduzida à luz da Teoria de Redes e Ações Coletivas, trata-se de uma pesquisa qualitativa e quantitativa, predominantemente exploratória, que utiliza do estudo de caso como método de coleta de dados e da cientometria como método de análise. O objeto de investigação foi constituído pela produção bibliográfica dos membros da ABPSEC, associados entre janeiro de 2020 a junho de 2021, considerando os trabalhos completos publicados em anais de eventos e os artigos publicados em periódicos nos últimos cinco anos (2016-2020). Após a análise final de 639 publicações, os resultados apontaram a existência de uma rede científica formada entre os membros da ABPSEC, com ênfase para os laços fortes e capitaneada por um núcleo de pesquisadores e instituições.
The Architecture, Engineering and Construction (AEC) industry is fraught with complex and difficult problems. Artificial intelligence (AI) represents a powerful tool to assist in addressing these ...problems. Therefore, over the years, researchers have been conducting research on AI in the AEC industry (AI-in-the-AECI). In this paper, the first comprehensive scientometric study appraising the state-of-the-art of research on AI-in-the-AECI is presented. The science mapping method was used to systematically and quantitatively analyze 41,827 related bibliographic records retrieved from Scopus. The results indicated that genetic algorithms, neural networks, fuzzy logic, fuzzy sets, and machine learning have been the most widely used AI methods in AEC. Optimization, simulation, uncertainty, project management, and bridges have been the most commonly addressed topics/issues using AI methods/concepts. The primary value and uniqueness of this study lies in it being the first in providing an up-to-date inclusive, big picture of the literature on AI-in-the-AECI. This study adds value to the AEC literature through visualizing and understanding trends and patterns, identifying main research interests, journals, institutions, and countries, and how these are linked within now-available studies on AI-in-the-AECI. The findings bring to light the deficiencies in the current research and provide paths for future research, where they indicated that future research opportunities lie in applying robotic automation and convolutional neural networks to AEC problems. For the world of practice, the study offers a readily-available point of reference for practitioners, policy makers, and research and development (R&D) bodies. This study therefore raises the level of awareness of AI and facilitates building the intellectual wealth of the AI area in the AEC industry.
•Genetic algorithms, neural networks, fuzzy logic, fuzzy sets, and machine learning are the most widely used AI methods in AEC.•Optimization, simulation, uncertainty, project management, and bridges are the most commonly addressed topics/issues using AI methods/concepts.•Future research opportunities lie in applying robotic automation to AEC problems.•There are future research opportunities also in using convolutional neural networks (CNNs) for solving AEC problems.
Topic modeling is a type of statistical model for discovering the latent “topics” that occur in a collection of documents through machine learning. Currently, latent Dirichlet allocation (LDA) is a ...popular and common modeling approach. In this paper, we investigate methods, including LDA and its extensions, for separating a set of scientific publications into several clusters. To evaluate the results, we generate a collection of documents that contain academic papers from several different fields and see whether papers in the same field will be clustered together. We explore potential scientometric applications of such text analysis capabilities.
•Green building research has recorded a steady growth between 1992 and 2018.•At least 44% of 195 countries are involved in green building research.•The global north makes the greatest contribution to ...green building research.•Existing studies revolve around ten (10) broad green building research areas.
Following the 1960s environmental movement and the energy crisis in the 70s, evidence spurred research on renewable energy and energy efficiency practices. As a result, the green building (GB) movement emerged in the 90s to promote buildings which are designed to reduce the consumption of energy, electricity, water, materials, natural resources as well as improve environmental performance and human health over the whole lifecycle. With a prime goal of improving energy efficiency, GB has gained recognition in national and international energy policies. Following manifold exemplary projects and testified benefits, GBs research has recorded a tremendous increase over the years. Thus, it is essential to monitor the research progress to identify areas that require further research. This paper recruited the bibliometric data of 1147 GBs research articles and conducted a scientometric review. The review showed that GBs research publications increased steadily from 1992 to 2018. This highlights the increasing commitment towards the initiative. The paper found that at least 44% of all countries in the world are involved in GBs research. Ten (10) broad GB research areas in existing studies were identified and discussed and areas for further research were proposed. Thus, the paper offers a useful reference point to early-stage researchers, funding authorities, energy policymakers and industry professionals on the research progress in GBs.
Practical interest in ‘computer vision’ has risen remarkably over the last 20 years, transforming the current state of construction-related research and attracting the worldwide attention of scholars ...and practitioners. This study conducts a scientometric review of the global research published between 1999 and 2019 on computer vision applications for construction, through co-author, co-citation, keyword and clustering analysis. A total of 1158 journals and conference proceedings from Scopus database were analyzed. Trends within the field are identified, as are the dominant sub-fields and their interconnections, as well as citation patterns, key publications, key research institutions, key researchers, and key journals, along with the extent to which these interact with each other in research networks. The provided results were analyzed to identify the deficiencies in current research and propose future trends. Among these is a bias in the research literature towards traditional on-site construction and a concerning gap of off-site construction research, as well as a lack of inter-relationships and collaboration between researched areas, the researchers themselves, and/or the research institutions. In the near future, computer vision will play a key role in the future development of smart construction and improvement of quality in construction projects. This study hopes to bring awareness to the industry, the journal editors, and the researchers of the need for a deeper exchange of ideas in any future research efforts.
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•A scientometric review of computer vision research for construction applications from 1999 to 2019 is performed.•1158 journal articles and conference proceedings are analyzed.•Research topics and trends are identified and visualized.•Limitations and gaps in the literature are discussed.
Agent-based computing is a diverse research domain concerned with the building of intelligent software based on the concept of “agents”. In this paper, we use Scientometric analysis to analyze all ...sub-domains of agent-based computing. Our data consists of 1,064 journal articles indexed in the ISI web of knowledge published during a 20 year period: 1990–2010. These were retrieved using a topic search with various keywords commonly used in sub-domains of agent-based computing. In our proposed approach, we have employed a combination of two applications for analysis, namely Network Workbench and CiteSpace—wherein Network Workbench allowed for the analysis of complex network aspects of the domain, detailed visualization-based analysis of the bibliographic data was performed using CiteSpace. Our results include the identification of the largest cluster based on keywords, the timeline of publication of index terms, the core journals and key subject categories. We also identify the core authors, top countries of origin of the manuscripts along with core research institutes. Finally, our results have interestingly revealed the strong presence of agent-based computing in a number of non-computing related scientific domains including Life Sciences, Ecological Sciences and Social Sciences.
In the construction industry under “Industry 4.0”, Natural Language Processing (NLP) has been widely used to process and analyze text data to achieve construction intelligence. However, there lacks a ...comprehensive review of NLP application in construction-related areas, raising bar of research entry and setting obstacles for the rapid development in this fields. Ninety one NLP-related research articles in construction-related fields were retrieved to conduct a scientometric analysis using CiteSpace and VOSViewer, and summarized from the perspectives of anchordatasets/data sources, technologies/tools, and applications and progress. The results show that data isolation causing non-reproducibility of research is one of the severe problems to be solved. Besides, pure NLP application studies will no longer meet the future industry development needs and more cross-modal interdisciplinary research based on the end-to-end pre-trained neural network model framework is needed. This study helps readers gain an in-depth understanding of the NLP application and development in construction.
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•91 NLP-related research articles (2000−2020) from Scopus and WOS were collected.•A systematic scientometric analysis was conducted using the tools of CiteSpace and VOSViewer.•A comprehensive review of the collected articles was carried out from three aspects.•The current challenges, possible solutions, and future research trends were critically discussed.
•The study applied science mapping approach in reviewing construction safety research.•Mainstream keywords such as BIM were identified in existing literature.•Influential journals, scholars, and ...articles in construction safety were evaluated.•An in-depth qualitative discussion identified existing research topics and limitations.•A research framework was proposed by linking mainstream topics into future research directions.
This study adopted a three-step holistic review approach consisting of bibliometric review, scientometric analysis, and in-depth discussion to gain a deeper understanding of the research development in construction safety. Focusing on a total of 513 journal articles published in Scopus, the influential journals, keywords, scholars, and articles in the domain of construction safety were analyzed. For example, simulation and fall from height related topics, although not with the highest occurrence of being studied, had the highest impact in terms of average citation received per year. It was found that research in the recent 10 years have been extended to the developing countries and regions with a more variety of research topics, such as BIM, and data mining, etc. Articles related to applying BIM in safety management received the highest average normalized citation. A follow-up qualitative discussion targeted three main objectives: summarizing mainstream research topics, identifying existing research gaps, and proposing future research directions. Five main categories were aligned, namely safety climate and safety culture, application of information technologies, worker-oriented safety, safety management program, and hazard recognition and risk assessment. Based on the above, a framework and future research directions were proposed which could serve both the academic community and practical fields in multiple themes within construction safety, including: an adaptable safety climate and safety culture model; prototypes, continuous development, and readiness of applying information technologies in safety management; subgroups factors linked to cognitive models of workers’ safety perceptions and behaviors; and artificial intelligence and smart technologies into safety program management.
The lack of predictability of citation-based measures frequently used to gauge impact, from impact factors to short-term citations, raises a fundamental question: Is there long-term predictability in ...citation patterns? Here, we derive a mechanistic model for the citation dynamics of individual papers, allowing us to collapse the citation histories of papers from different journals and disciplines into a single curve, indicating that all papers tend to follow the same universal temporal pattern. The observed patterns not only help us uncover basic mechanisms that govern scientific impact but also offer reliable measures of influence that may have potential policy implications.
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