Mapping the knowledge domain of road safety studies: A scientometric analysis

Green roof development knowledge map: A review of visual analysis using CiteSpace and VOSviewer

Green roofs are generally acknowledged as environmentally sustainable roof systems with several environmental, economic, and social benefits, as well as an effective and practical strategy for mitigating the negative consequences of urbanization. In this paper, we used CiteSpace and VOSviewer bibliometric software for visual analysis, citation analysis, co-authorship network, co-citation analysis, and keyword analysis for descriptive statistics on 3986 articles on "green roofs" published in the Web of Science core database since 2000. Descriptive statistics were used for citation analysis, co-authorship network, co-citation analysis, and keyword analysis. According to a review of green roofing-related research literature, (1) Through analysis from three dimensions of country, institution, and author, it was found that China, the United States, and Italy ranked among the top three countries in terms of green roof publication volume; All but three of the top 10 institutions in terms of publications are from China and all are from developed countries; A large-scale collaborative network has not yet formed among authors. (2) Through keyword clustering analysis, it was found that "green roof," "performance," and "UHI" were the three keywords with the highest frequency. The research direction of this theme mainly includes five primary themes: rainwater management, urban biodiversity, building energy efficiency, alleviating urban heat islands and improving air quality, sustainable development, and public health. Through keyword hot words, it is found that the frequency of occurrence is relatively high, mainly involving energy conservation, alleviating urban heat islands, biodiversity, and sustainable development. The research on sustainable development, its impact on urban microclimate, and air quality remains a hot topic through keyword highlighting. (3) Co-citation analysis was used to identify the most influential journals, highly cited publications, and authors. (4) Three potential study objectives have been identified: synergistic development with other green infrastructures from an urban planning standpoint, localized research on green roofs, and photovoltaic green roofs.

Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends

One of the main causes of death is out-of-hospital cardiac arrest (OHCA), which has a poor prognosis and poor neurological outcomes. This phenomenon has attracted increasing attention. However, there is still no published bibliometric analysis of OHCA. This bibliometric analysis of publications on OHCA aimed to visualize the current status of research, determine the frontiers of research, and identify future trends. Publications on OHCA were downloaded from the web of science database. The data elements included year, countries/territories, institutions, authors, journals, research areas, citations of publications, etc. Joinpoint regression and exponential models were used to identify and predict the trend of publications, respectively. Knowledge domain maps were applied to conduct contribution and collaboration, cooccurrence, cocitation, and coupled analyses. Timeline and burst detection analysis were used to identify the frontiers in the field. A total of 3 219 publications on OHCA were found from 1998 to 2022 (average annual percentage change = 16.7; 95% CI 14.4, 19.1). It was estimated that 859 articles and reviews would be published in 2025. The following research hotpots were identified: statement, epidemiology, clinical care, factors influencing prognosis and emergency medical services. The research frontier identification revealed that 7 categories were classified, including therapeutic hypothermia, emergency medical services, airway management, myocardial infarction, extracorporeal cardiopulmonary resuscitation, stroke foundation and trial. The burst detection analysis revealed that percutaneous coronary intervention, neurologic outcome, COVID-19 and extracorporeal cardiopulmonary resuscitation are issues that should be given continual attention in the future. This bibliometric analysis may reflect the current status and future frontiers of OHCA research.

Understanding the domain of driving distraction with knowledge graphs

This paper aims to provide insight into the driving distraction domain systematically on the basis of scientific knowledge graphs. For this purpose, 3,790 documents were taken into consideration after retrieving from Web of Science Core Collection and screening, and two types of knowledge graphs were constructed to demonstrate bibliometric information and domain-specific research content respectively. In terms of bibliometric analysis, the evolution of publication and citation numbers reveals the accelerated development of this domain, and trends of multidisciplinary and global participation could be identified according to knowledge graphs from Vosviewer. In terms of research content analysis, a new framework consisting of five dimensions was clarified, including "objective factors", "human factors", "research methods", "data" and "data science". The main entities of this domain were identified and relations between entities were extracted using Natural Language Processing methods with Python 3.9. In addition to the knowledge graph composed of all the keywords and relationships, entities and relations under each dimension were visualized, and relations between relevant dimensions were demonstrated in the form of heat maps. Furthermore, the trend and significance of driving distraction research were discussed, and special attention was given to future directions of this domain.

Knowledge mapping of targeted immunotherapy for myasthenia gravis from 1998 to 2022: A bibliometric analysis

Background

The treatment of myasthenia gravis (MG) has advanced from steroids and traditional immunosuppressants to targeted immunotherapy. Targeted immunotherapy has been successfully employed in clinical practice in recent years. This study aimed to explore the emerging trend of targeted immunotherapy in MG and summarize the knowledge structure through bibliometric methods.

Methods

The Web of Science Core Collection database (WoSCC) was chosen to retrieve the literature on targeted immunotherapy for MG. Two bibliometric analysis software, VOSviewer and CiteSpace, and bibliometric online platform were mainly used to evaluate the contributions from countries/regions, institutions, journals, and authors through the construction and visualization of bibliometric networks. By systematically reviewing a knowledge domain, future research developments were determined. The R version 4.1.2 and Microsoft Excel 365 were used for statistical analysis.

Results

A total of 562 original articles and 262 reviews relevant to MG targeted immunotherapy were included. The number of publications on targeted immunotherapy for MG exhibited a two-phase advancement. The first stage showed a steady growth trend from 1998 to 2016, with an annual number of no more than 35 publications. The second stage revealed an explosive growth trend from 2017, reaching a peak number of publications in 2020. The United States ranked first in the number of publications, citations, and h-index. The author with the highest citation and h-index was Vincent A. And 28.03% of the articles were published in the top 10 journals. In addition to “myasthenia gravis”, the keyword with the highest consideration was “rituximab”, followed by “double-blind”, which indicate research hotspots gradually from basic research to clinical research over time, especially in the field of targeted immunotherapy. The MG treatment has entered a personalized precision treatment phase. Exploration into new target molecules and conducting high-quality randomized controlled trials on existing biological agents are the further research direction.

Conclusion

The current study summarized the global research trends concerning targeted immunotherapy for MG. Research interests gradually advanced from basic research to clinical research. MG treatment has entered a personalized precision treatment phase. Further investigations into new target molecules and high-quality randomized controlled trials on existing biological agents are required urgently to direct future immunotherapy research.

Mapping pedestrian safety studies between 2010 and 2021: A scientometric analysis

Pedestrian deaths constitute 23% of road traffic deaths globally. Although several research papers have contributed to pedestrian safety analysis, they did not provide a comprehensive overview of the progress in the research domain and publication trends. This makes it difficult to identify trends and insights into the pedestrian research domain in light of the voluminous number of papers. This study fills this gap with a scientometric analysis of research on pedestrian safety analysis indexed in the Web of Science. The scope covers 2594 papers published between 2010 and 2021 in English. This study analyzed the annual publications and citation trends, top ten most cited papers, influential papers in their first three years after publication, contributing authors, funding agencies, and contributing journals. The regional gaps between the proportion of pedestrian deaths and research were also analyzed. The results showed low research productivity from low and middle-income countries although they have a high incidence of pedestrian deaths. Subsequently, the main keyword clusters or frontier topics were identified and topic analysis was employed to identify the evolution of studies. Four keyword clusters were identified, i.e., "vehicle-to-pedestrian crash and injury severity analysis", "pedestrian movement and decision simulation experiments", "improving the vehicle system towards reducing body region impact injuries", "pedestrian behavior in crosswalks and signalized intersections". This study contributes an integrated knowledge map of pedestrian safety analysis, publication trends, the evolution of studies, and under-researched topics to guide future research work in pedestrian safety analysis.

A 20-year bibliometric analysis of Fuchs endothelial corneal dystrophy: from 2001 to 2020

PURPOSE

The aim of this study was to identify trends and focuses in the field of Fuchs endothelial corneal dystrophy (FECD) research.

METHODS

A bibliometric analysis based on the Web of Science Core Collection was conducted. All publications related to FECD from 2001 to 2020 were extracted and analyzed. VOSviewer v.1.6.17 was used to construct a visualization map and evaluate the trends and focuses in FECD research.

RESULTS

A total of 1,041 publications were extracted. The rate of global publications has steadily increased. The United States produced the highest number of publications (461), the highest number of citations (18,757), and the highest H index (69). Melles GRJ published the highest number of papers (60), and Price FW had the highest number of citations (4,154) in the FECD research field. The highest number of publications came from the journal Cornea (279). Keywords were classified into four clusters: (1) corneal transplantation surgery, (2) surgical techniques and instruments, (3) corneal parameter measurement, and (4) genetic and molecular pathomechanisms. The average appearing years (AAYs) of the keywords were evaluated. Recently appearing keywords included "Tcf4 gene" (AAY of 2018.3), "ctg18.1" (AAY of 2017.2), "trinucleotide repeat expansion" (AAY of 2018.3), "rock inhibitor" (AAY of 2017.4), and "descemetorhexis" (AAY of 2017.4).

CONCLUSIONS

The United States has a dominant position in FECD research. Although corneal transplantation surgery has been the most mainstream area of FECD research field for a long time, gene mutations such as the TCF4 CTG trinucleotide repeat expansion, nonsurgical interventions such as rho-associated kinase inhibitors, and newer surgical methods such as descemetorhexis without endothelial keratoplasty are potential research hotspots.

Deep Journalism and DeepJournal V1.0: A Data-Driven Deep Learning Approach to Discover Parameters for Transportation

We live in a complex world characterised by complex people, complex times, and complex social, technological, economic, and ecological environments. The broad aim of our work is to investigate the use of ICT technologies for solving pressing problems in smart cities and societies. Specifically, in this paper, we introduce the concept of deep journalism, a data-driven deep learning-based approach, to discover and analyse cross-sectional multi-perspective information to enable better decision making and develop better instruments for academic, corporate, national, and international governance. We build three datasets (a newspaper, a technology magazine, and a Web of Science dataset) and discover the academic, industrial, public, governance, and political parameters for the transportation sector as a case study to introduce deep journalism and our tool, DeepJournal (Version 1.0), that implements our proposed approach. We elaborate on 89 transportation parameters and hundreds of dimensions, reviewing 400 technical, academic, and news articles. The findings related to the multi-perspective view of transportation reported in this paper show that there are many important problems that industry and academia seem to ignore. In contrast, academia produces much broader and deeper knowledge on subjects such as pollution that are not sufficiently explored in industry. Our deep journalism approach could find the gaps in information and highlight them to the public and other stakeholders.

Highway Planning Trends: A Bibliometric Analysis

An efficient highway infrastructure network is a determining factor in promoting the socio-economic development of countries and regions. Highway planning activities are highly important because their results ensure that projects are delivered within budget, schedule, and scope. Therefore, academics and professionals have promoted various methodological and technological advances focused on improving highway planning processes, evidenced by many scientific documents that address the topic. Despite progress, few studies have focused on analyzing the state of the knowledge structure and the technological and methodological trends of the highway planning topic. Considering this gap, this study presents trends in highway planning and its knowledge structure based on a bibliometric analysis from January 2015 to September 2021. The research method is based on a bibliometric analysis composed of five main stages: (1) scope definition, (2) selection of bibliometric analysis techniques, (3) data collection, (4) bibliometric analysis execution, and (5) evidence analysis and synthesis. Information from 1703 journal papers was collected and analyzed. The findings show that the main trends of highway planning focus on life cycle analysis, computational tools, smart cities, sustainability issues, construction processes, new equipment and materials, and multi-objective optimization, among others. Thus, the findings of this study allow the reader to identify the methodological and technological trends in highway planning and their knowledge gaps to guide future studies in the field.

Visualization and Analysis of Mapping Knowledge Domain of Heterogeneous Traffic Flow

Mapping knowledge domain (MKD) is an important application in bibliometrics, which is a method of visually presenting and explaining newly developed interdisciplinary scientific fields using data mining, information analysis, scientific measurement, and graphic rendering. This study combines applied mathematics, visual analysis technology, information science, and scientometrics to systematically analyze the development status, research distribution, and future trend of the heterogeneous traffic flow by using the MKD software tools VOSviewer and CiteSpace. Based on the MKD and Bibliometrics approaches, 4709 articles have been studied, which were published by Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) from 2004 to 2021 in the field of heterogeneous traffic flows. Firstly, this paper presents the annual numbers of articles, origin countries, main research organizations, and groups as well as the source journals on heterogeneous traffic flow studies. Then, cocitation analysis is used to divide heterogeneous traffic flow into three main research directions, which include “heterogeneous traffic flow model,” “traffic flow capacity analysis,” and “traffic flow stability analysis.” The keyword cooccurrence analysis is applied to identify five dominant clusters: “modeling and optimization methods,” “traffic flow characteristics analysis,” “driving behavior analysis,” “simulation experiment,” and “policies and barriers.” Finally, burst keywords were studied according to the publication date to present more clearly the change of research focus and direction over time.

Ergonomics 4.0: A bibliometric review of Human Factors research in Industrial Revolution 4.0 (IR 4.0)

BACKGROUND

The scientometric study is a visualization method used to collect big data from databases, to explore the relationships between citing and co-cited documents and then visualize the results. Unlike the new term Ergonomics 4.0, bibliometric analysis has been studied in various related fields of Ergonomics.

OBJECTIVE

The aim of this study was to create a bibliometric analysis in related field of Ergonomics and Fourth Industrial Revolution. This analysis can shed light on the new developed research field in both sides of the present study, occupational ergonomics and industry 4.0.

METHODS

After selecting related keywords, Advance search was done in Scopus and Web of Science. Bibliometric results were presented by these databases' analyzer and by exported data to VOS viewer software. No time or language restriction was applied.

RESULTS

Retrieved Articles were 104 and 285 for Web of Science and Scopus respectively. The frequent co-occurrences for keywords were seen between "industry 4.0" and "Human Factors". The USA and Germany were also the most productive countries in this field. Well-known Ergonomics journals had low participation in the Evolution of Ergonomics and Fourth Industrial Revolution topics.

CONCLUSION

Due to more participation of industry 4.0-related researchers in this topic, it is recommended that ergonomists from around the world, and especially Eastern countries, attempt to conduct research in this field. Furthermore, devoting some forth-coming special issues in this field is recommended to top ergonomics journals.

The Landscape of Risk Communication Research: A Scientometric Analysis

Risk communication is a significant research domain with practical importance in supporting societal risk governance and informed private decision making. In this article, a high-level analysis of the risk communication research domain is performed using scientometrics methods and visualization tools. Output trends and geographical patterns are identified, and patterns in scientific categories determined. A journal distribution analysis provides insights into dominant journals and the domain’s intellectual base. Thematic clusters and temporal evolution of focus topics are obtained using a terms analysis, and a co-citation analysis provides insights into the evolution of research fronts and key documents. The results indicate that the research volume grows exponentially, with by far most contributions originating from Western countries. The domain is highly interdisciplinary, rooted in psychology and social sciences, and branching mainly into medicine and environmental sciences. Narrative themes focus on risk communication in medical and societal risk governance contexts. The domain originated from public health and environmental concerns, with subsequent research fronts addressing risk communication concepts and models. Applied research fronts are associated with environmental hazards, public health, medical risks, nuclear power, and emergency response to various natural hazards. Based on the results, various avenues for future research are described.