Mapping Knowledge in the Economic Areas of Green Building Using Scientometric Analysis

This paper presents the first inclusive scientometric review of the economic areas of green building (GBE). The aim is to methodically examine and summarize the state-of-the-art of the GBE body of knowledge. To this end, this study analyses 1713 GBE-related bibliographic records retrieved from the Web of Science by using the quantitative method of knowledge mapping. The knowledge base, knowledge domain, and knowledge evolution of how they interacted with each other are explored using document co-citation analysis and keywords co-citation analysis of the existing body of literature. The research findings are informative in recognizing and interpreting the underlying structure and trends in GBE. A knowledge map provides a valuable and instructive understanding of the evolution and status quo of the GBE knowledge body, as well as assisting in recognizing the gaps and deficiencies involved. The results will help in understanding how GBE knowledge is evolving and its role played in green building, and thus provide suggestions of how academic research can enhance sustainability practices in terms of economic area in the future.

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Mapping the knowledge domains of value management: a bibliometric approach

Engineering Construction & Architectural Management ◽

10.1108/ecam-06-2018-0252 ◽

2019 ◽

Vol 26 (3) ◽

pp. 499-514 ◽

Cited By ~ 7

Author(s):

E.M.A.C. Ekanayake ◽

Geoffrey Shen ◽

Mohan M. Kumaraswamy

Keyword(s):

Knowledge Base ◽

Bibliometric Analysis ◽

Value Management ◽

Knowledge Map ◽

Knowledge Mapping ◽

Knowledge Domain ◽

Evolutionary Trajectory ◽

Content Type ◽

Mapping Tool ◽

Future Demands

PurposeThe purpose of this paper is to review the state-of-the-art of literature of value management (VM) and to map the VM domain to provide a launch pad for further knowledge development and dissemination.Design/methodology/approachThis study employed CiteSpace bibliometric analysis software to systematically, comprehensively and accurately review the VM-related literature and to map the VM knowledge domain.FindingsThe results reveal the current VM knowledge base, clusters, research hotspot, and the evolutionary trajectory while contributing to the development of VM knowledge by providing a dynamic platform for integrating future developments in research.Originality/valueThe contribution of this paper to scientific VM knowledge is, therefore, a quantitative and accurate VM knowledge map based on a bibliometric analysis of data from the VM knowledge base, domains and evolution. The findings can be generalised and used as an effective knowledge mapping tool in a specific field of study that could complement and add significant value to the often adopted more traditional literature reviews. This study further recommends that the proposed knowledge map be frequently updated by similar future studies to fill gaps that arise with changing needs, priorities and contexts, as well as to identify corresponding future demands in the VM research domain.

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Bibliometric analysis and mapping knowledge domain of pterygium: 2000-2019

International Journal of Ophthalmology ◽

10.18240/ijo.2021.06.17 ◽

2021 ◽

Vol 14 (6) ◽

pp. 903-914

Author(s):

Yu-Chi Wang ◽

◽

Qian Liu ◽

Zi-Yan Yu ◽

Jing Wang ◽

...

Keyword(s):

Citation Analysis ◽

Web Of Science ◽

Knowledge Structure ◽

The United States ◽

Annual Number ◽

Knowledge Map ◽

Knowledge Domain ◽

The Past ◽

Number Of Publications ◽

Cluster 2

AIM: To track the knowledge structure, topics in focus, and trends in emerging research in pterygium in the past 20y. METHODS: Base on the Web of Science Core Collection (WoSCC), studies related to pterygium in the past 20y from 2000-2019 have been included. With the help of VOSviewer software, a knowledge map was constructed and the distribution of countries, institutions, journals, and authors in the field of pterygium noted. Meanwhile, using co-citation analysis of references and co-occurrence analysis of keywords, we identified basis and hotspots, thereby obtaining an overview of this field. RESULTS: The search retrieved 1516 publications from WoSCC on pterygium published between 2000 and 2019. In the past two decades, the annual number of publications is on the rise and fluctuated a little. Most productive institutions are from Singapore but the most prolific and active country is the United States. Journal Cornea published the most articles and Coroneo MT contributed the most publications on pterygium. From co-occurrence analysis, the keywords formed 3 clusters: 1) surgical therapeutic techniques and adjuvant of pterygium, 2) occurrence process and pathogenesis of pterygium, and 3) epidemiology, and etiology of pterygium formation. These three clusters were consistent with the clustering in co-citation analysis, in which Cluster 1 contained the most references (74 publications, 47.74%), Cluster 2 contained 53 publications, accounting for 34.19%, and Cluster 3 focused on epidemiology with 18.06% of total 155 co-citation publications. CONCLUSION: This study demonstrates that the research of pterygium is gradually attracting the attention of scholars and researchers. The interaction between authors, institutions, and countries is lack of. Even though, the research hotspot, distribution, and research status in pterygium in this study could provide valuable information for scholars and researchers.

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Mapping the Knowledge Domain of Smart-City Research: A Bibliometric and Scientometric Analysis

Sustainability ◽

10.3390/su11236648 ◽

2019 ◽

Vol 11 (23) ◽

pp. 6648 ◽

Cited By ~ 11

Author(s):

Li Zhao ◽

Zhi-ying Tang ◽

Xin Zou

Keyword(s):

Big Data ◽

Smart City ◽

Applied Research ◽

Citation Index ◽

Smart Cities ◽

Knowledge Bases ◽

Scientometric Analysis ◽

Knowledge Mapping ◽

Knowledge Domain ◽

Research Frontiers

As urbanization continues to accelerate, the number of cities and their growing populations have created problems, such as the congestion and noise related to transportation, the pollution from industry, and the difficulty of disposing of garbage. An emerging urban strategy is to make use of digital technologies and big data to help improve the quality of life of urban residents. In the past decade, more and more researchers have studied smart cities, and the number of literature in this field grows rapidly, making it “big data”. With the aim of better understanding the contexts of smart-city research, including the distribution of topics, knowledge bases, and the research frontiers in the field, this paper is based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) in the Web of Science (WoS) Core Collection, and the method used is that of comprehensive scientometric analysis and knowledge mapping in terms of diversity, time slicing, and dynamics, using VOSviewer and CiteSpace to study the literature in the field. The main research topics can be divided into three areas—“the concepts and elements of the smart city”, “the smart city and the Internet of Things”, and “the smart city of the future”—through document co-citation analysis. There are four key directions—“research objectives and development-strategy research”, “technical-support research”, “data-processing and applied research”, and “management and applied research”—analyzed using keywords co-occurrence. Finally, the research frontiers are urban-development, sustainable cities, cloud computing, artificial intelligence, integration, undertaken through keyword co-occurrence analysis.

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Document- and Keyword-based Author Co-citation Analysis

Data and Information Management ◽

10.2478/dim-2018-0009 ◽

2018 ◽

Vol 2 (2) ◽

pp. 70-82 ◽

Cited By ~ 2

Author(s):

Binglu Wang ◽

Yi Bu ◽

Win-bin Huang

Keyword(s):

Citation Analysis ◽

Semantic Similarity ◽

Method Validation ◽

New Method ◽

Global Network ◽

Network Visualization ◽

Knowledge Domain ◽

Knowledge Domains ◽

Domain Mapping ◽

The Relationship

AbstractIn the field of scientometrics, the principal purpose for author co-citation analysis (ACA) is to map knowledge domains by quantifying the relationship between co-cited author pairs. However, traditional ACA has been criticized since its input is insufficiently informative by simply counting authors’ co-citation frequencies. To address this issue, this paper introduces a new method that reconstructs the raw co-citation matrices by regarding document unit counts and keywords of references, named as Document- and Keyword-Based Author Co-Citation Analysis (DKACA). Based on the traditional ACA, DKACA counted co-citation pairs by document units instead of authors from the global network perspective. Moreover, by incorporating the information of keywords from cited papers, DKACA captured their semantic similarity between co-cited papers. In the method validation part, we implemented network visualization and MDS measurement to evaluate the effectiveness of DKACA. Results suggest that the proposed DKACA method not only reveals more insights that are previously unknown but also improves the performance and accuracy of knowledge domain mapping, representing a new basis for further studies.

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The theme trends and knowledge structure of H19 gene in cancer research: a scientometric analysis (Preprint)

10.2196/preprints.16722 ◽

2019 ◽

Author(s):

Zhigang Cui ◽

Zhihua Yin ◽

Lei Cui

Keyword(s):

Cancer Research ◽

Social Network ◽

Citation Analysis ◽

High Frequency ◽

Cancer Metastasis ◽

Intellectual Structure ◽

Scientometric Analysis ◽

Research Areas ◽

Pivotal Study ◽

Matrix Construction

BACKGROUND Background:H19 gene is maternally expressed imprinted oncofetal gene. This study aimed to explore distribution pattern and intellectual structure of H19 in cancer. OBJECTIVE Published scientific 826 papers related to H19 from Jan 1st, 2000 to March 22st, 2019 were obtained from the Web of Science core collection. METHODS We performed extraction of keywords and co-word matrix construction using BICOMB software. Then gCLUTO software, ucinet, excel software, Citespace, Vosviewer were successfully used for double -cluster analysis, social network analysis, Strategic coordinate analysis, co-citation analysis, and journal analysis. RESULTS We analyzed the distributions of included article of H19, identified 34 high-frequency keywords and classified them into 6 categories. Through co-word analysis and co-citation analysis for these categories, we identified the hotspot areas and intellectual basis about H19 in cancer research. Then the prospects of hotspots and their associations were accesssed by strategic coordinate diagrams and social network diagrams. CONCLUSIONS 6 research categories of 34 high-frequency keywords could represent the theme trends on H19 to some extent. Mir-675, cancer metastasis and risk, Wnt/β-catenin signaling pathway, SNP, and ceRNA network were core and mature research areas in this field. There is a lack of promising areas of H19 research. Matouk(2006) article play a key role in H19 research, and Murphy SK(2006)and Luo M(2013) articles serve knowledge transmission as pivotal study.

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Questions to the Article of research output and international cooperation among countries during the COVID-19 pandemic (Preprint)

10.2196/preprints.26576 ◽

2020 ◽

Author(s):

Shu-Chun Kuo ◽

Tsair-Wei Chien ◽

Willy Chou

Keyword(s):

Citation Analysis ◽

International Cooperation ◽

Web Of Science ◽

Research Output ◽

Visual Representations ◽

Scientometric Analysis ◽

Medical Subject Headings ◽

Pubmed Central ◽

The Us ◽

Circle Diagram

UNSTRUCTURED We read with great interest the study by Grammes et al. on research output and international cooperation among countries during the COVID-19 pandemic. The paper is a quantitative study using scientometric analysis instead of a qualitative research using citation analysis. A total of 7,185 publications were extracted from Web of Science Core Collection (WoS) with keywords of “covid19 OR covid-19 OR sarscov2 OR sars-cov-2” as of July 4, 2020. We replicated a citation analysis study to extract abstracts from Pubmed Central(PMC) with similar keywords mentioned above and obtained 35,421 articles relevant to COVID-10 matching their corresponding number of citation in PMC. one hundred top-cited atricles were selected and compared on diagrams. Social network analysis combined with citation numbers in articles was performed to analyze international cooperation among countries. The results were shown on a world map instead of the circle diagram in the previous study. A Sankey diagram was applied to highlight entities(e.g., countries, article types, medical subject headings, and journals) with the most citations. Authors from Chian dominated citations in these 100 top-cited articles rather than the US in publications addressed in the previous study. Both visual representations of the world map and Sankey diagram were provided to readers with a better understanding of the research output and international cooperation among countries during the COVID-19 pandemic

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Research on the Literature of Green Building Based on the Web of Science: A Scientometric Analysis in CiteSpace (2002–2018)

Sustainability ◽

10.3390/su11133716 ◽

2019 ◽

Vol 11 (13) ◽

pp. 3716 ◽

Cited By ~ 11

Author(s):

Yingling Shi ◽

Xinping Liu

Keyword(s):

Web Of Science ◽

Green Building ◽

Development Trend ◽

Status Quo ◽

Future Research ◽

Building Industry ◽

Scientometric Analysis ◽

The Past ◽

Evolution Pattern ◽

The Status

Since the 21st century, the concept of green building has been gradually popularized and implemented in more countries, which has become a popular direction in the area of sustainability in the building industry. Over the past few decades, many scholars and experts have done extensive research on green building. The purpose of this paper is to systematically analyze and visualize the status quo of green building. Therefore, based on Web of Science (WoS), this paper analyzed the existing knowledge system of green building using CiteSpace, identified keywords related to green building and their frequency of occurrence using the function of keyword co-occurrence analysis, recognized five clusters using the function of cluster analysis, and explored the knowledge evolution pattern of green building using citation bursts analysis in order to reveal how research related to green building has evolved over time. On the basis of aforementioned keywords, clusters, and citation bursts analysis, this paper has built a knowledge graph for green building. This paper can help readers to better understand the status quo and development trend of green building and to easier recognize the shortcomings in the development of green building, so as to provide a promising direction for future research.

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