Knowledge map analysis of China's public participation in environmental governance PPP project using CiteSpace

China’s public participation in environmental governance PPP projects has become a hot research issue.Based on the CiteSpace software,taking 1592 literatures collected by CNKI from 2000 to 2021 as samples,the paper visually analyzes the literature timing,author distribution,institutional distribution,hot topics and evolution trends of Chinese public participation in environmental governance PPP project.After 20 years of development,the research focus of China’s public participation in environmental governance PPP project involves rural environmental governance,environmental diversification governance,regional environmental governance and environmental governance value-driven,and shows endogenous implicit drive and endogenous explicit drive.The multi-spiral characteristics of China’s public participation in environmental governance PPP coexist with endogenous implicit obstacles and exogenous implicit obstacles.

The bibliometrics survey of ecological economic research:A knowledge mapping analysis based on the SCI and SSCI database

Based on bibliometrics and knowledge mapping analysis method,this paper uses CiteSpace,a visual literature analysis tool,to analyze 3794 related documents with the theme of“economic economy”in SCI and SSCI databases from 2010 to 2020,including authors,institutions,subject headings and literature co-citation,so as to reveal the development and hot spots of ecological economic research.The results show that in recent years,the number of documents on ecological economic research has been increasing,and developed countries are dominant.China’s research in this field has developed rapidly and has certain advantages in terms of quantity and quality.The institution with the largest number of papers is Chinese Academy Science,followed by Beijing Normal University,University of Chinese Academy of Sciences,Peking University and Universitat autonomy de Barcelona;research hotspots in recent 10 years include“sustainability”,“management”,“climate change”,“impact”,“economy”,“china”,“conservation”,“ecosystem service”,etc.The top three journals are Sustainability,Journal of Cleaner Production,and Ecological Economics,accounting for about 10%of the total number of papers published.The hot spots of ecological economic research in 2010-2020 can be divided into three stages,with different theme words emerging in each stage.From 2018 to 2020,the theme word of high-strength emergence is“anthropocene”,which indicates that“anthropocene”may be the focus of future research.

CONSTRUCTION METHOD OF KNOWLEDGE MAP BASED ON DESIGN PROCESS

Due to the increasing amount and complexity of knowledge in product design, the know-ledge map based on design process is presented as a tool to reuse product design process, promote the product design knowledge sharing. The relationship between design task flow and knowledge flow is discussed; A knowledge organizing method based on design task decomposition and a visualization method to support the knowledge retrieving and sharing in product design are proposed. And a knowledge map system to manage the knowledge in product design process is built with Visual C＋＋ and SVG. Finally, a brief case study is provided to illustrate the construction and application of knowledge map in fuel pump design.

Visualizing risk factors of dementia from scholarly literature using knowledge maps and next-generation data models

Scholarly communication of knowledge is predominantly document-based in digital repositories,and researchers find it tedious to automatically capture and process the semantics among related articles.Despite the present digital era of big data,there is a lack of visual representations of the knowledge present in scholarly articles,and a time-saving approach for a literature search and visual navigation is warranted.The majority of knowledge display tools cannot cope with current big data trends and pose limitations in meeting the requirements of automatic knowledge representation,storage,and dynamic visualization.To address this limitation,the main aim of this paper is to model the visualization of unstructured data and explore the feasibility of achieving visual navigation for researchers to gain insight into the knowledge hidden in scientific articles of digital repositories.Contemporary topics of research and practice,including modifiable risk factors leading to a dramatic increase in Alzheimer’s disease and other forms of dementia,warrant deeper insight into the evidence-based knowledge available in the literature.The goal is to provide researchers with a visual-based easy traversal through a digital repository of research articles.This paper takes the first step in proposing a novel integrated model using knowledge maps and next-generation graph datastores to achieve a semantic visualization with domain-specific knowledge,such as dementia risk factors.The model facilitates a deep conceptual understanding of the literature by automatically establishing visual relationships among the extracted knowledge from the big data resources of research articles.It also serves as an automated tool for a visual navigation through the knowledge repository for faster identification of dementia risk factors reported in scholarly articles.Further,it facilitates a semantic visualization and domain-specific knowledge discovery from a large digital repository and their associations.In this study,the implementation of the proposed model in the Neo4j graph data repository,along with the results achieved,is presented as a proof of concept.Using scholarly research articles on dementia risk factors as a case study,automatic knowledge extraction,storage,intelligent search,and visual navigation are illustrated.The implementation of contextual knowledge and its relationship for a visual exploration by researchers show promising results in the knowledge discovery of dementia risk factors.Overall,this study demonstrates the significance of a semantic visualization with the effective use of knowledge maps and paves the way for extending visual modeling capabilities in the future.

Research Status and Trends of Science and Technology Evaluation in China—Visual Analysis Based on Knowledge Mapping

In order to understand the current status and future trends of China’s science and technology evaluation research, we use the visual analysis tool CiteSpace to use the source journals included in the Chinese social science citations from 1998-2019 as the data source, and evaluate the domestic science and technology evaluation papers from the number of publications, the co-occurrence of authors, Institutional co-occurrence and subject clustering are analyzed. The study found that: the total amount of literature in the field of domestic science and technology evaluation is showing an overall upward trend;a relatively obvious author cooperation network has been formed, but the core author group has not yet been formed;institutional cooperation clusters have appeared, but the cooperation between institutions is still relatively scattered;The research topics focus on three aspects: science and technology evaluation index system, evaluation method and evaluation system.

Multi-action-based approach for constructing knowledge map

To alleviate the information overload in the product design process,this work proposes a multiaction-based method for constructing knowledge map. Since the relationships of knowledge are implicit in the collected user activities,the method calculates the similarity according to the collected user activities.Three concepts,including knowledge,action and user,are explained first. Based on this,the similarity calculation method is illustrated in detail. The dependencies of actions and relations of the user are considered in the calculation method. Further,the approach of applying the constructed knowledge map to alleviate information overload is proposed. At last,the proposed method is validated by a knowledge search and result comparison experiment.

Visualization Analysis for China’s Business Schools Accreditation Studies Based on Knowledge Mapping

The aim of the paper is to identify and explore leading thematic areas within the research field related to Business Schools Accreditation in China.Based on data from the China National Knowledge Infrastructure(CNKI)database,the keywords frequency was analyzed,and the theory of mapping knowledge domain was used to visualize the keywords co-occurrence network to make further research of the heated issues.The findings indicate that the research scope involved in business school accreditation research is broad,and research content focus on teaching,management,talent cultivation.According to the results of keywords co-occurrence analysis of different stages,AACSB,AACSB Accreditation,international accreditation,business school,AOL,internationalization,accreditation are the most important issues to business school research in China,given their position and role in the research network.The paper generates the added value mainly from the point of view of theory development.

Visualization Analysis of Research on Student Classroom Engagement by Knowledge Mapping

The aim of the paper is to identify and explore leading development situation within the research field related to student classroom engagement.Using knowledge mapping tools,this paper conducted the visualization analysis on internationalliteraturein relation to student classroom engagementfrom the Web of Science databases.By combination of the statistical data and visualizationmapping,this paper studied on the research relationship networks and status for the co-authors'countries/institutions,co-citation documents/journalsand co-occurring keywordsbased on the sample datafromliterature.The results indicate that the number ofpublished papershasincreased obviously and expanded graduallysince 2000.Main countries and institutions of researches were the UnitedStates,Australia,United Kingdom,Canada and China in order,and these countries had intense collaboration.The theoretical basis of the research come from education and teaching,psychology.The hotspots of researches fromthe global literature coveredvarious fields including achievement,motivation,behavior,education,performance.As a result of the multidisciplinary integration,many relevant internationalresearch constantly expanded the research scopes,which promoted the combination and development of theories.

Traffic accidents of autonomous vehicles based on knowledge mapping:A review

As a characteristic representative of the new generation of vehicles,autonomous driving is expected to improve people's driving experience.The study on traffic accident of autonomous vehicles(AVs)helps provide suggestions for autonomous driving safety from multiple disciplines and perspectives,and provide support for formulating traffic accident treatment schemes.Knowledge mapping,as a cutting-edge research method in bibliometrics,scientifically and objectively displays the relevant research status using visual means.This paper uses CiteSpace 6.1.r3 to analyze 5068 related literature on the Web of Science database from 1991 to 2022 and finds out major thematic clusters,important documents and representative journals according to citation frequency.The results show that research on traffic accidents involving AVs focuses on accident preventing technologies,including how to avoid collisions,track lane-position,and enhance vehicle-toeverything(V2X)communication.This paper extracts the mean research topics and key points involved in the field and illustrates journals related to AVs and traffic accidents,which provides guidance for subsequent researchers to carry out in-depth research and contribute their papers.Popular journals are in disciplines of mathematics,systems,computer,economics,and social science.This paper also suggests scholars to consider the aspects of scene reconstruction,cause analysis,and injury of vulnerable road users,so as to investigate traffic accidents and put forward effective treatment schemes to reduce AV accidents,and ultimately improve road safety.

Research Progress on Economic Forest Water Stress Based on Bibliometrics and Knowledge Graph

This study employed the bibliometric software CiteSpace 6.1.R6 to analyze the correlation between thermal infrared,spectral remote sensing technology,and the estimation of economic forest water stress.It aimed to review the development and current status of this field,as well as to identify future research trends.A search was conducted on the China National Knowledge Infrastructure(CNKI)database using the keyword“water stress”for relevant studies from 2003 to 2023.The visual analysis function of CNKI was used to generate the distribution of annual publication volume,and CiteSpace 6.1.R6 was utilized to create network maps illustrating collaboration among authors and institutions.The study also analyzed the hotspots and frontiers of economic forest water stress.As a result,a total of 6664 academic journal articles related to water stress were retrieved.Considerable collaboration networks were observed among scholars and institutions,with a focus on using crown temperature monitoring to diagnose crop water stress.Based on the research findings,it was evident that the primary research trend involved the use of thermal infrared and spectral remote sensing technology for estimating water stress,making it a future research hotspot.

Global perspectives and future research directions for the phytoremediation of heavy metal-contaminated soil:A knowledge mapping analysis from 2001 to 2020

In total,9,552 documents were extracted from the Web of Science Core Collection and subjected to knowledge mapping and visualization analysis for the field of phytoremediation of HM-contaminated soil(PHMCS)with CiteSpace 5.7 R3 software.The results showed that(1)the number of publications increased linearly over the studied period.The top 10 countries/regions,institutions and authors contributing to this field were exhibited.(2)Keyword co-occurrence cluster analysis revealed a total of 8 clusters,including“Bioremediation,”“Arsenic,”“Biochar,”“Oxidative stress,”“Hyperaccumulation,”“EDTA,”“Arbuscular mycorrhizal fungi,”and“Environmental pollution”clusters(3)In total,334 keyword bursts were obtained,and the 25 strongest,longest duration,and newest keyboard bursts were analyzed in depth.The strongest keyword burst test showed that the hottest keywords could be divided into 7 groups,i.e.,“Plant bioremediation materials,”“HM types,”“Chelating amendments,”“Other improved strategies,”“Bioremediation characteristics,”“Risk assessment,”and“Other.”Almost half of the newest topics had emerged in the past 3 years,including“biochar,”“drought,”“health risk assessment,”“electrokinetic remediation,”“nanoparticle,”and“intercropping.”(4)In total,9 knowledge base clusters were obtained in this study.The studies of Ali et al.(2013),Blaylock et al.(1997),Huang et al.(1997),van der Ent et al.(2013),Salt et al.(1995),and Salt(1998),which had both high frequencies and the strongest burst scores,have had the most profound effects on PHMCS research.Finally,future research directions were proposed.

Mapping the knowledge of international Chinese medicines treatment on type 2 diabetes:A biblimetrical study

Objective:To uncover and identify the hot topic and frontier of Chinese medicines treatment of type 2 diabetes mellitus(T2DM).Methods:Web of Science TM was searched for published articles for Chinese medicines treatment of T2DM ranging from January 1st,2002 to July 6th,2016.Knowledge maps of the international Chinese medicines treatment of T2DM are visualized by using document cooccurrence analysis and word frequency analysis(Institution and Journal),co-citation clustering analysis(Co-reference),keyword co-occurrence clustering analysis with CiteSpac III,a tool of scientometrics.Results:Universidad Nacional Autonoma de Mexico is the institution with the highest number of published papers that had been cited in this field,while China has four institutions among the top 10.The journal of the highest frequency of co-cited journal was Diabetes Care,a core one in the field.Keywords co-occurrence network was composed of 185 nodes,541 lines,and divided into 10 clusters.Co-citation network of co-reference was composed of 407 nodes,1199 lines,and divided into 20 clusters.Using Chinese medicine to improve insulin resistance and Chinese medicine research on blood glucose control are the hot topics.The frontier contains two aspects:new drugs development and application of intestinal insulin treatment and development and use of traditional Chinese medicine antidiabetic plants.Conclusion:Institutions from China still plays a major role in TCM-focused T2DM studies.The effect of TCM herbs on insulin resistance is the hot topic of the domain.Developing new TCM herbal medicine that regulates incretin effect is the domain frontier.Research on the Chinese medicines treatment of T2DM needs more high-quality evidence to support,and its mechanism requires further exploration.

Knowledge Map Mining of Financial Data

The Knowledge Map （KM） concept, which was derived to describe and manage knowledge. KM provides insight into the from the Fuzzy Cognitive Map （FCM）, is used interdependencies and uncertainties contained in the system. This paper uses a model-free method to mine KMs in historical data to analyze component stock corporations of the Shanghai Stock 50 index. The analyses use static and time-domain analyses. The results indicate that a knowledge map is useful for representing knowledge and for monitoring the health of companies. Furthermore, sudden changes of the key features of the KMs should be taken seriously by policymakers as an alarm of a crisis.

Analysis of Visualization Mapping in the Field of Brand Community Based on Cite Space Ⅲ

Taking 887 relevant papers in the Web of Science database as the analysis object,and with the help of Citespace III software developed by Chen Chaomei s team,this study makes a visual mapping analysis of the brand community field from the perspective of research hotspots,cooperation between countries(regions)and institutions,and co-citation networks.The study has found that research hotspots in this field focus on brand community,community,consumer,internet,model,loyalty,word-of-mouth,impact and trust.The United States has absolute strength in leading the research frontier of this field,and the degree of cooperation within the country is higher than that of international cooperation.The core papers in this field were published in from authoritative journals in the field of management.Through the analysis of the core papers,readers can further understand the development context of the brand community field.

Research Progress and Trends in Organizational Resilience Research: Knowledge Graph Analysis Based on CiteSpace

Organizational resilience is an important core element for today’s companies to turn around in the VUCA1 environment. It can strengthen the ability of companies to adapt and help them to regain their strength in adversity. In this paper, based on CNKI database and WOS (Web of Science) database search to get the Chinese and foreign literature (special reference to English literature) for the whole year 2000-2022, and use bibliometric method to analyze the hot spots and research trends in the field of organizational resilience research, the results found that: 1) there is more foreign-language research literature on tissue toughness than Chinese-language research literature, and the number of articles published in Chinese journals on this topic has entered a rapid growth phase since 2011, and the number of articles published both at home and abroad is generally on the rise, and tissue toughness is increasingly becoming a research hotspot;2) from the cooperation of existing published literature, the cooperation network between research scholars is generally more dispersed, and domestic scholars are mostly independent;3) From the viewpoint of research hotspots, individual resilience, supply chain resilience and risk management are hotspots in foreign organizational resilience research;domestic research mainly focuses on the connotation and measurement dimensions of organizational resilience, individual resilience and dynamic capabilities.

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

AIM:To track the knowledge structure,topics in focus,and trends in emerging research in pterygium in the past 20 y.METHODS:Base on the Web of Science Core Collection(Wo SCC),studies related to pterygium in the past 20 y 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 cocitation 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 Wo SCC 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 cooccurrence 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 cocitation 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.

Study Progress Analysis of Effluent Quality Prediction in Activated Sludge Process Based on CiteSpace

In this paper, CiteSpace, a bibliometrics software, was adopted to collect research papers published on the Web of Science, which are relevant to biological model and effluent quality prediction in activated sludge process in the wastewater treatment. By the way of trend map, keyword knowledge map, and co-cited knowledge map, specific visualization analysis and identification of the authors, institutions and regions were concluded. Furthermore, the topics and hotspots of water quality prediction in activated sludge process through the literature-co-citation-based cluster analysis and literature citation burst analysis were also determined, which not only reflected the historical evolution progress to a certain extent, but also provided the direction and insight of the knowledge structure of water quality prediction and activated sludge process for future research.

Science Mapping:A Systematic Review of the Literature

Purpose： We present a systematic review of the literature concerning major aspects of science mapping to serve two primary purposes： First, to demonstrate the use of a science mapping approach to perform the review so that researchers may apply the procedure to the review of a scientific domain of their own interest, and second, to identify major areas of research activities concerning science mapping, intellectual milestones in the development of key specialties, evolutionary stages of major specialties involved, and the dynamics of transitions from one specialty to another.Design/methodology/approach： We first introduce a theoretical framework of the evolution of a scientific specialty. Then we demonstrate a generic search strategy that can be used to construct a representative dataset of bibliographic records of a domain of research. Next, progressively synthesized co-citation networks are constructed and visualized to aid visual analytic studies of the domain＇s structural and dynamic patterns and trends. Finally, trajectories of citations made by particular types of authors and articles are presented to illustrate the predictive potential of the analytic approach.Findings： The evolution of the science mapping research involves the development of a number of interrelated specialties. Four major specialties are discussed in detail in terms of four evolutionary stages： conceptualization, tool construction, application, and codification. Underlying connections between major specialties are also explored. The predictive analysis demonstrates citations trajectories of potentially transformative contributions.Research limitations： The systematic review is primarily guided by citation patterns in the dataset retrieved from the literature. The scope of the data is limited by the source of the retrieval, i.e. the Web of Science, and the composite query used. An iterative query refinement is possible if one would like to improve the data quality, although the current approach serves our purpose adequately. More in-depth analyses of each specialty would be more revealing by incorporating additional methods such as citation context analysis and studies of other aspects of scholarly publications.Practical implications： The underlying analytic process of science mapping serves many practical needs, notably bibliometric mapping, knowledge domain visualization, and visualization of scientific literature. In order to master such a complex process of science mapping, researchers often need to develop a diverse set of skills and knowledge that may span multiple disciplines. The approach demonstrated in this article provides a generic method for conducting a systematic review.Originality/value： Incorporating the evolutionary stages of a specialty into the visual analytic study of a research domain is innovative. It provides a systematic methodology for researchers to achieve a good understanding of how scientific fields evolve, to recognize potentially insightful patterns from visually encoded signs, and to synthesize various information so as to capture the state of the art of the domain.

Research fronts and researchers of World Journal of Psychiatry in 2023: A visualization and analysis of mapping knowledge domains

BACKGROUND In the rapidly evolving landscape of psychiatric research,2023 marked another year of significant progress globally,with the World Journal of Psychiatry(WJP)experiencing notable expansion and influence.AIM To conduct a comprehensive visualization and analysis of the articles published in the WJP throughout 2023.By delving into these publications,the aim is to deter-mine the valuable insights that can illuminate pathways for future research endeavors in the field of psychiatry.METHODS A selection process led to the inclusion of 107 papers from the WJP published in 2023,forming the dataset for the analysis.Employing advanced visualization techniques,this study mapped the knowledge domains represented in these papers.RESULTS The findings revealed a prevalent focus on key topics such as depression,mental health,anxiety,schizophrenia,and the impact of coronavirus disease 2019.Additionally,through keyword clustering,it became evident that these papers were predominantly focused on exploring mental health disorders,depression,anxiety,schizophrenia,and related factors.Noteworthy contributions hailed authors in regions such as China,the United Kingdom,United States,and Turkey.Particularly,the paper garnered the highest number of citations,while the American Psychiatric Association was the most cited reference.CONCLUSION It is recommended that the WJP continue in its efforts to enhance the quality of papers published in the field of psychiatry.Additionally,there is a pressing need to delve into the potential applications of digital interventions and artificial intelligence within the discipline.

Construction of Intelligent Recommendation Retrieval Model of FuJian Intangible Cultural Heritage Digital Archives Resources

In order to improve the consistency between the recommended retrieval results and user needs,improve the recommendation efficiency,and reduce the average absolute deviation of resource retrieval,a design method of intelligent recommendation retrieval model for Fujian intangible cultural heritage digital archive resources based on knowledge atlas is proposed.The TG-LDA(Tag-granularity LDA)model is proposed on the basis of the standard LDA(Linear Discriminant Analysis)model.The model is used to mine archive resource topics.The Pearson correlation coefficient is used to measure the relevance between topics.Based on the measurement results,the FastText deep learning model is used to achieve archive resource classification.According to the classification results,TF-IDF(term frequency–inverse document frequency)algorithm is used to calculate the weight of resource retrieval keywords to achieve resource retrieval,and a recommendation model of intangible cultural heritage digital archives resources is built through the knowledge map to achieve comprehensive and personalized recommendation of resources.The experimental results show that the recommendation and retrieval results of the proposed method are more in line with users’needs,can provide users with personalized digital archive resources,and the average absolute deviation of resource retrieval is low,the recommendation efficiency is high,and the utilization effect of archive resources is effectively improved.