Knowledge Mapping Analysis Research Articles

Research on Uncertainty of Landslide Susceptibility Prediction—Bibliometrics and Knowledge Graph Analysis

Landslide prediction is one of the complicated topics recognized by the global scientific community. The research on landslide susceptibility prediction is vitally important to mitigate and prevent landslide disasters. The instability and complexity of the landslide system can cause uncertainty in the prediction process and results. Although there are many types of models for landslide susceptibility prediction, they still do not have a unified theoretical basis or accuracy test standard. In the past, models were mainly subjectively selected and determined by researchers, but the selection of models based on subjective experience often led to more significant uncertainty in the prediction process and results. To improve the universality of the model and the reliability of the prediction accuracy, it is urgent to systematically summarize and analyze the performance of different models to reduce the impact of uncertain factors on the prediction results. For this purpose, this paper made extensive use of document analysis and data mining tools for the bibliometric and knowledge mapping analysis of 600 documents collected by two data platforms, Web of Science and Scopus, in the past 40 years. This study focused on the uncertainty analysis of four key research subfields (namely disaster-causing factors, prediction units, model space data sets, and prediction models), systematically summarized the difficulties and hotspots in the development of various landslide prediction models, discussed the main problems encountered in these four subfields, and put forward some suggestions to provide references for further improving the prediction accuracy of landslide disaster susceptibility.

Knowledge Areas and New Trends in Lumbar Disc Herniation Research: Bibliometrics and Knowledge Mapping Analysis.

To determine the coalitions and impact of authors, countries, institutions, and journals, evaluate the knowledge base, find the hotspot trends, and identify the emerging topics in lumbar disc herniation (LDH). The articles related to LDH were obtained from the Web of Science Core Collection on August 21, 2021. Two scientometric software (CiteSpace 5.8.R.1 and VOSviewer 1.6.17) were used to perform bibliometric and knowledge-map analysis. From the set parameters, 4642 articles were included in the literature. Although the total number of publications fluctuated between 2001 and 2020, a general trend toward increase was observed. Respectively, the most productive country and institution in the field were the United States and Wooridul Spine Hospital. The most active and cited authors were Lee and Weinstein. Spine was the most impactful and cited journal. Weinstein (JAMA 296:2441-2450, 2006) had the highest number of co-citations and Weinstein(N Engl J Med 358:794-810, 2008) had the highest number of citations. The keyword "low back pain" was ranked first for frequency and total link strength, whereas "risk factor" was ranked first for centrality. Topics including pathogenesis (disc herniation), examination methods (MRI), treatment methods (non-surgical treatment, surgical treatment), surgical options (laminectomy, discectomy), clinical observations (double-blind, efficacy, outcome, learning curve), and evaluation of efficacy (meta-analysis) of LDH have been the focus of leading-edge research in 2001-2020. Using bibliometric methods, this study mapped the knowledge map of LDH research in the past 20years. The study identifies existing trends to provide a framework for further research.

Roles and Research Trends of Neuroscience on Major Information Systems Journal: A Bibliometric and Content Analysis.

Over the past decade, neuroscience has been integrated into information systems as a new methodology and perspective to study and solve related problems. Therefore, NeuroIS has emerged as a new cutting-edge research field. This review aimed to identify, summarize, and classify existing NeuroIS publications through knowledge mapping and bibliometric analysis. To effectively understand the development trend of NeuroIS, this study referred to the journal selection index of the Association of Business Schools in 2021 and journals above three stars in the field of information management as the main selection basis. A total of 99 neuroscience papers and their citation data were included from 19 major information systems journals of SCI/SSCI. This study analyzed bibliometric data from 2010 to 2021 to identify the most productive countries, universities, authors, journals, and prolific publications in NeuroIS. To this end, VOSviewer was used to visualize mapping based on co-citation, bibliographic coupling, and co-occurrence. Keywords with strong citation bursts were also identified in this study. This signifies the evolution of this research field and may reveal potential research directions in the near future. In selecting research methods and analysis tools for NeuroIS, content analysis was used to further conclude and summarize the relevant trends. Moreover, a co-citation network analysis was conducted to help understand how the papers, journals, and authors in the field were connected and related, and to identify the seminal or pioneering major literature. For researchers, network maps visualized mainstream research and provided a structural understanding of NeuroIS. The review concludes by discussing potential research topics in this field.

Interprofessional corporation between registered community nurses and general practitioner: A qualitative study

Interprofessional corporation between registered community nurses and general practitioner: A qualitative study Abstract. Background: The quality and effectiveness of the work of certified nurses and physicians in the inpatient setting is significantly influenced by interprofessional collaboration (IPC). There is a lack of knowledge about IPC in outpatient primary care at home. Aim: In highlighting the differences between inpatient and outpatient settings, the challenges of IPC for the outpatient setting should become clear. Method: The data for this study was collected in interprofessional group discussions. The data were methodically extracted by knowledge mapping and structuring content analysis according to Kuckartz (2018). The results were compared with the meta-matrix for interprofessional collaboration in inpatient settings by Schärli et al. (2017). Results: The qualitative analysis showed that the outpatient IPC of qualified nurses and general practitioners is challenged by structural conditions, which are given in the inpatient area by the form of organization. Lack of agreements and coordination of processes complicate IPC in outpatient health care, as there is no recognized common management structure. Conclusions: In order to ensure that IPC in the outpatient setting is not dependent on the individual commitment of individuals, nurses and GPs must jointly define criteria for their IPC, define processes and communication channels, and develop a common approach and team spirit.

Treatment of Liver Fibrosis: A 20-Year Bibliometric and Knowledge-Map Analysis.

Objectives: To analyze the research hotspots, evolution, and trends of the treatment of liver fibrosis in the recent 20 years, bibliometric and knowledge-map analysis were used. Methods: Publications associated with the treatment of liver fibrosis were retrieved from the Web of Science Core Collection on 16 April 2022. CiteSpace 5.8.R3 and VOSviewer 1.6.18 were calculated to perform bibliometric and knowledge-map analysis. Results: A total of 72,686 authors from 200 institutions in 134 countries/regions published 15,237 studies in different academic journals. United States was the most productive country, and Shanghai Jiao Tong University was the most published institution. Trauner Michael had the most published articles, whereas Scott L. Friedman was the most frequently co-cited author. Moreover, there was frequent inter-institution cooperation between countries in the years 2015 and after, but the before years showed rare inter-institution cooperation. The journal HEPATOLOGY was both the most published publication and the most frequently co-cited one in this field. Screened keywords, such as virus infection, inflammation, oxidative stress, activation of hepatic stellate cell (HSC), and hepatocellular apoptosis, could be both therapeutic targets and pathological mechanisms in terms of liver fibrosis. Furthermore, long-term suppression of hepatitis B virus replication and the activation of HSC were the latest hotspots and topics related to the treatment of liver fibrosis. Besides, the treatments of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis were also involved in the treatment of liver fibrosis, which were both emerging topics and rapidly developing hot fields. Conclusion: This bibliometric analysis conducted a full overview of the treatment of liver fibrosis, which provided important clues and ideas for scholars focusing on this field. Not only that, the field is still in a stage of rapid development and will continue to be a research hotspot in the future.

Knowledge Domain and Emerging Trends of Social Vulnerability Research: A Bibliometric Analysis (1991-2021).

Carrying out social vulnerability research has become an important way to understand the sustainable development of resources, the environment, populations, and societies. Clarifying the research context and development trend of social vulnerability is of great significance to the follow-up theoretical research on and practical exploration of sustainable social development. With the help of a CiteSpace knowledge map analysis, this study reveals the research hotspots and their evolution in different periods and puts forward the key problems in and future direction of social vulnerability research in the future. This study found that the number of articles on social vulnerability research showed a steady upward trend and that the research experienced roughly three stages: an embryonic stage, a development stage, and a stable stage. The United States, Brazil, the United Kingdom, and China accounted for the majority of the research, but the intensity of cooperation between them is still weak. Vulnerability assessment and risk assessment in the context of policy and environmental change are hot topics in the current research. In the future, it is necessary to focus on the comprehensive research on the integrated and cross-scale research on social vulnerability, research on its occurrence and evolution, and on the dynamic monitoring as well as optimal regulation of social vulnerability under multiple pressures.

Knowledge Map Analysis of Industry–University Research Cooperation Policy Research Based on CNKI and WOS Visualization in China

The field of industry–university research cooperation policy is about to enter a new stage. It is necessary to systematically sort and summarize the literature, both at home and abroad, that has been produced in recent years. Through knowledge map analysis of the current situation regarding the development of industry–university research cooperation policy, from both domestic and foreign perspectives, taking the core documents included in the Web of Science and China National Knowledge Infrastructure database as samples, and through visual research on the time context, author, organization, theme, and other key nodes of industry–university research cooperation policy research, with the help of CiteSpace and NoteExpress measurement software, we can draw the following conclusions. Domestic research is relatively focused on colleges and universities; that is, industry–university research cooperation as a mechanism to cultivate innovative talents and improve scientific research and enhance social services, while foreign countries pay more attention to the technological utilization and technological innovation of enterprises and their accompanying economic benefits. Domestic and foreign research have their own characteristics, and the research quality of the two is equal. Generally speaking, research on the policy of domestic university research cooperation should focus on the following three points in the future: It must be closely related to the functions of colleges and universities, the nature of enterprises, and social needs; we must attach great importance to empirical research; and we must pay attention to cross-organizational research.

Characteristics, Progress and Trends of Urban Microclimate Research: A Systematic Literature Review and Bibliometric Analysis

Climate change has been a hot topic in recent years. However, the urban microclimate is more valuable for research because it directly affects people’s living environments and can be adjusted by technological means to enhance the resilience of cities in the face of climate change and disasters. This paper analyses the literature distribution characteristics, development stages, and research trends of urban microclimate research based on the literature on “urban microclimate” collected in the Web of Science core database since 1990, using CiteSpace and VOSviewer bibliometric software. It is found that the literature distribution of the urban microclimate is characterized by continuous growth, is interdisciplinary, and can be divided into four stages: nascent exploration, model quantification, diversified development and ecological synergy. Based on the knowledge mapping analysis of keyword clustering, annual overlap, and keyword highlighting, it can be predicted that the research on foreign urban land patch development has three hot trends—multi-scale modelling, multi-factor impact, and multi-policy guidance. The study’s findings help recognize the literature distribution characteristics and evolutionary lineage of urban microclimate research and provide suggestions for future urban microclimate research.

A visual knowledge map analysis of mine fire research based on CiteSpace.

Mine fire has always been a serious disaster in coal industry; many academic achievements have poured out in the past two decades for solving this problem. In this study, visual analysis was conducted to grasp the hotspots and development trend of mine fire research. Papers that published in 1999-2020 were retrieved as the data basis from Web of Science, and CiteSpace was used to carry out knowledge map analysis. The results shown that number of papers has increased steadily since 2005 and achieved explosive growth since 2014. Deng J is the first published author among many scholars. China, the USA, and Australia are active areas in mine fire research and China University of Mining and Technology ranks first in this field. The highest co-occurrence frequency keyword is "spontaneous combustion." International Journal of Coal Geology and Fuel provide guidance for mine fire research. Fire prevention technology, low carbon, ecology, and sustainable development are the hot research in recent years. The prevention and control of mine fire from combustion mechanism should be further strengthened.

Exploring a body of knowledge for promoting the building information model for facility management

The aim of this research is to explore the body of knowledge on BIM-enabled facility management (BIM-FM). This study proposes a method for knowledge mapping analysis through scientometric analysis, which uses two software, VOSviewer, and CiteSpace, to analyze the results of literature data related to BIM-FM. 319 journal articles were collected for collaborative network analysis, co-occurrence network analysis, and co-citation network analysis. The findings of the study conclude that 1) the knowledge structure of BIM-FM was divided into five significant clusters; 2) the key research topics of BIM-FM show an evolutionary trend in different periods, from model construction, framework, and gradually expanding to implementation, system integration, and smart building; 3) future research foresees three research directions, including enhancing the application of BIM in multiple facility management; advanced applications in facility management; health and safety for facility managers; and improving regulations and risk awareness.

Visual Analysis of Global Carbon Mitigation Research Based on Scientific Knowledge Graphs.

Global temperature change is related to the destiny of all mankind, and carbon mitigation, as well as greenhouse gases control, are key points. In order to explore the basic knowledge, research hotspots and trends in global carbon mitigation research, this paper, based on 15,304 carbon mitigation articles from Web of Science, from 1991 to 2021, conducts spatio-temporal distribution, country distribution, research hotspots and cooperation network analysis, and draws frontier knowledge graphs of carbon mitigation by using CiteSpace, Gephi and other scientific knowledge mapping and literature analysis software. The key scholars, important literature, main contribution institutions and countries/regions in the field of carbon mitigation research were extracted, and the research basis and evolution law were displayed. The study found that: (1) The research on carbon mitigation is increasing every year, which can be roughly divided into four stages: germination, low-speed development, medium-speed development and high-speed development. (2) The spatial distribution of carbon mitigation research is unbalanced, mainly showing a characteristic of “one super and many strong” centered on the United States. (3) The research hotspots of carbon mitigation have gradually evolved from phenomenon analysis, policy guidance, method exploration to mechanism improvement. Further research might focus on ocean carbon sink, carbon trading and carbon-negative technology.

Knowledge mapping analysis of mental health research on COVID-19

Knowledge mapping analysis of mental health research on COVID-19

Correction to: Publication characteristics, topic trends and knowledge domains of karst ecological restoration: a bibliometric and knowledge mapping analysis from 1991 to 2021

Correction to: Publication characteristics, topic trends and knowledge domains of karst ecological restoration: a bibliometric and knowledge mapping analysis from 1991 to 2021

Analysis of CiteSpace knowledge map for traditional Chinese medicine prevention and treatment of cerebral small vessel diseases

This study aims to analyze the research on the prevention and treatment of cerebral small vessel diseases(CSVDs) with traditional Chinese medicine(TCM) based on knowledge map, and to preliminarily explore the research hotspots and trends. To be specific, articles on TCM treatment of CSVDs in CNKI, Wanfang, and VIP(from establishment to November 2021) were retrieved, followed by bibliometric analysis. Then CiteSpace 5.7 R4 and Gephi were employed for generation of maps on annual number of articles, author cooperation, institution cooperation, keyword co-occurrence, keyword clustering, and keyword emergence. A total of 106 eligible articles were screened out, and the annual number of articles presented a steady upward trend. A total of 277 authors were included in the author cooperation network, among whom CHEN Zhigang published the most articles. A total of 87 institutions were included in the institution cooperation network, among which Dongfang Hospital of Beijing University of Chinese Medicine showed the most frequent cooperation with other institutions. Keyword clustering showed that research on the TCM treatment of CSVDs mainly focused on five aspects: related disease research, neurological function deficits, disease nature and location in TCM, TCM treatment methods, and formulas. The prevention and treatment of CSVDs with TCM in China has been developing steadily in the past ten years, and TCM has unique advantages in the prevention and treatment of this disease. The knowledge maps vividly demonstrated the development and research hotspots and trends in this field. The result is expected to provide a reference for further research in this field.

Scientometric Analysis of COVID-19 Scholars Publication using Machine Learning

The global health crisis that started in December 2019 resulted in an outbreak of coronavirus named COVID-19. Scientists worldwide are working to demystify the transmission and pathogenic mechanisms of the deadly coronavirus. The World Health Organization has declared COVID-19 a pandemic in March 2020, which makes it essential to track and analyse the research state of COVID-19 for guidance on further research. This research was conducted using scientometric analysis, knowledge-mapping analysis, COVID-19 studies and journal classifications. The publications used in this study include over 3000 COVID-19 papers made available to the public from 1 January 2018 to 15 April 2021 in the PubMed databases. In this study, it was discovered that the rapid reaction of researchers worldwide resulted in a fast growth trend between 2019 and 2021 in the number of publications related to COVID-19. It was discovered that the largest number of studies is in the United States of America, which is one of the countries most affected by a pandemic. The method adopted for this study involved the use of documents such as Case Reports (CAT), Journal Article (JAT), letter (LTR), EAT, and Editorial (EDT). This is followed by the classification of COVID-19 related publications that were retrieved from PubMed between 2019 and 2021 using machine learning (ML) models such as Naïve Bayes (NB), Bayesian Generalized Linear Model (BGL), Heteroscedastic Discriminant Analysis (HDA) and Multivariate Adaptive Regression Spline (MAR). Simulation results show that the classification accuracy of MAR is better than that of other ML models used in this study. The sensitivity of the MAR is within the range of 100%. This shows that MAR performs better than NB, BGL and HDA. MAR performs better with an overall accuracy of 89.62%. Our results show a high degree of strong collaboration in coronavirus research and the exchange of knowledge in the global scientific community.

Analysis of visual knowledge map of forest resources based on CiteSpace

Forest is the main body of the land ecosystem and the material infrastructure for the survival and development of human society. Research in the field of forest resources has a significant impact on the sustainability of forestry and the development of the national economy. In order to objectively reflect the research situation in the field of forest resources in my country, this paper makes a scientometric analysis of a series of literatures on the research field of forest resources selected from the CNKI database. The authors used CiteSpace software to visualize Forest Resources in the scientific field. This paper reveals the current research status of forest resources in my country, and then further analyzes the research hotspots in the field of forest resources, so that the analysis results can provide reference for future forest resources research.

Publication characteristics, topic trends and knowledge domains of karst ecological restoration: a bibliometric and knowledge mapping analysis from 1991 to 2021

Publication characteristics, topic trends and knowledge domains of karst ecological restoration: a bibliometric and knowledge mapping analysis from 1991 to 2021

Knowledge Mapping Analysis of Public Health Emergency Management Research Based on Web of Science.

At present, major public health emergencies frequently occur worldwide, and it is of great significance to analyze the research status and latest developments in this field to improve the ability of public health emergency management in various countries. This paper took 5,143 related studies from 2007 to 2020 from the Web of Science as research object and used CiteSpace, VOSviewer, and other software to perform co-word analysis, social network analysis, and cluster analysis. The results and conclusions were as follows: (1) the related research identified three periods: the exploration, growth, and outbreak period; (2) chronologically: the relevant research evolved from medical and health care for major diseases to emergency management and risk assessment of public health emergencies and then researched the novel coronavirus (COVID-19) pneumonia epidemic; (3) clustering analysis of high-frequency keywords, identifying three research hotspots: “disaster prevention and emergency medical services,” “outbreak and management of infectious diseases in Africa,” and “emergency management under the COVID-19 pneumonia epidemic.” Finally, this study combined the data and literature analysis to point out possible future research directions: from the research of the COVID-19 pneumonia epidemic to the research of general major public health emergencies, thinking and remodeling of the national public health emergency management system, and exploring the establishment of an efficient international emergency management cooperation mechanism.

Retrospection and prospect of embeddedness theory -- knowledge map analysis based on bibliometrics

Retrospection and prospect of embeddedness theory -- knowledge map analysis based on bibliometrics

Predicting Infectious Diseases: A Bibliometric Review on Africa.

Africa has a long history of novel and re-emerging infectious disease outbreaks. This reality has attracted the attention of researchers interested in the general research theme of predicting infectious diseases. However, a knowledge mapping analysis of literature to reveal the research trends, gaps, and hotspots in predicting Africa’s infectious diseases using bibliometric tools has not been conducted. A bibliometric analysis of 247 published papers on predicting infectious diseases in Africa, published in the Web of Science core collection databases, is presented in this study. The results indicate that the severe outbreaks of infectious diseases in Africa have increased scientific publications during the past decade. The results also reveal that African researchers are highly underrepresented in these publications and that the United States of America (USA) is the most productive and collaborative country. The relevant hotspots in this research field include malaria, models, classification, associations, COVID-19, and cost-effectiveness. Furthermore, weather-based prediction using meteorological factors is an emerging theme, and very few studies have used the fourth industrial revolution (4IR) technologies. Therefore, there is a need to explore 4IR predicting tools such as machine learning and consider integrated approaches that are pivotal to developing robust prediction systems for infectious diseases, especially in Africa. This review paper provides a useful resource for researchers, practitioners, and research funding agencies interested in the research theme—the prediction of infectious diseases in Africa—by capturing the current research hotspots and trends.