The hot issues of studies in China on digital information resources: Based on co-word analysis

With the SPSS and the help of factor method and hierarchical clustered method,journal articles on digital information resources(DIR) from CNKI in the past ten years are analyzed with a co-word analytical method in this paper. The hot issues of studies on DIR and the relationship between those subjects are analyzed in this investigation as well.

Co-word clustering analysis for nursing safety management research focuses by PubMed

Objective： To analyze hot research areas and the present research status of nursing safety management in PubMed. Methods： PubMed was searched using ＂safety management＂ for the literature on nursing safety management. BICOMB 2.0 and SPSS 20.0 software were used to analyze high-frequency keywords and conduct co-word clustering analysis. Results： We searched for totally 2353 articles related to our topic and extracted 19 high-frequency keywords （27.50%）. Five research focuses were concluded, including： study on nursing safety culture; team work to promote nursing safety; practice of nursing safety management; workplace violence against nursing staffs; nursing safety and quality evaluation standard. Conclusion： Analysis of the hotspots of nursing safety management in the past 10 years will contribute to understanding the research emphases and trend of development, and provide reference for the study and practice of nursing safety management.

Mapping theme trends and knowledge structures for human neural stem cells:a quantitative and co-word biclustering analysis for the 2013-2018 period

Neural stem cells,which are capable of multi-potential differentiation and self-renewal,have recently been shown to have clinical potential for repairing central nervous system tissue damage.However,the theme trends and knowledge structures for human neural stem cells have not yet been studied bibliometrically.In this study,we retrieved 2742 articles from the PubMed database from 2013 to 2018 using "Neural Stem Cells" as the retrieval word.Co-word analysis was conducted to statistically quantify the characteristics and popular themes of human neural stem cell-related studies.Bibliographic data matrices were generated with the Bibliographic Item Co-Occurrence Matrix Builder.We identified 78 high-frequency Medical Subject Heading(MeSH)terms.A visual matrix was built with the repeated bisection method in gCLUTO software.A social network analysis network was generated with Ucinet 6.0 software and GraphPad Prism 5 software.The analyses demonstrated that in the 6-year period,hot topics were clustered into five categories.As suggested by the constructed strategic diagram,studies related to cytology and physiology were well-developed,whereas those related to neural stem cell applications,tissue engineering,metabolism and cell signaling,and neural stem cell pathology and virology remained immature.Neural stem cell therapy for stroke and Parkinson’s disease,the genetics of microRNAs and brain neoplasms,as well as neuroprotective agents,Zika virus,Notch receptor,neural crest and embryonic stem cells were identified as emerging hot spots.These undeveloped themes and popular topics are potential points of focus for new studies on human neural stem cells.

Structures and dynamics of scientific knowledge networks:An empirical analysis based on a co-word network

Co-word networks are constructed with author-provided keywords in academic publications and their relations of co-occurrence.As special form of scientific knowledge networks,they represent the cognitive structure of scientific literature.This paper analyzes the complex structure of a co-word network based on 8,190 author-provided keywords extracted from 3,651 papers in five Chinese core journals in the field of management science.Small-world and scale-free phenomena are found in this network.A large-scale co-word network graph,which consists of one major giant component and many small isolated components,has been generated with the GUESS software.The dynamic growth of keywords and keyword co-occurrence relationships are described with four new informetrics measures.The results indicate that existing concepts always serve as the intellectual base of new ideas as represented by keywords.

Research status and hotspots of economic evaluation in nursing by co-word clustering analysis

Objective:The aim of this study is to discover research status and hotspots of economic evaluation(EE)in nursing area using co-word cluster analysis.Methods:Medical Subject Heading(MeSH)term“cost–benefit analysis”was searched in PubMed and nursing journals were limited by the function of filter.The information of author,country,year,journal,and keywords of collected paper was extracted and exported to Bicomb 2.0 system,where high-frequency terms and other data could be further mined.SPSS 19.0 was used for cluster analysis to generate dendrogram.Results:In all,3,020 articles were found and 10,573 MeSH terms were detected;among them,1,909 were MeSH major topics and generated 42 high-frequency terms.The consequence of dendrogram showed seven clusters,representing seven research hotspots:skin administration,infection prevention,education program,nurse education and management,EE research,neoplasm patient,and extension of nurse function.Conclusions:Nursing EE research involved multiple aspects in nursing area,which is an important indicator for decision-making.Although the number of papers is increasing,the quality of study is not promising.Therefore,further study may be required to detect nurses’knowledge of economic analysis method and their attitude to apply it into nursing research.More nursing economics course could carry out in nursing school or hospitals.

基于改进Co-word分析法的脆弱性数据分析技术研究

针对脆弱性信息系统中脆弱性数据质量保证问题,研究基于改进Co-word分析法的脆弱性数据分析技术。依据脆弱性分类法分类特征确定分析关键字,通过对Co-word分析法的改进设计了脆弱性数据分析算法,实现了脆弱性信息系统中脆弱性数据的验证、完善和补充。

Big data in healthcare:Conceptual network structure,key challenges and opportunities

Big data is a concept that deals with large or complex data sets by using data analysis tools(e.g.,data mining,machine learning)to analyze information extracted from several sources systematically.Big data has attracted wide attention from academia,for example,in supporting patients and health professionals by improving the accuracy of decision-making,diagnosis and disease prediction.This research aimed to perform a Bibliometric Performance and Network Analysis(BPNA)supported by a Scoping Review(SR)to depict the strategic themes,thematic evolution structure,main challenges and opportunities related to the concept of big data applied in the healthcare sector.With this goal in mind,4857 documents from the Web of Science covering the period between 2009 to June 2020 were analyzed with the support of SciMAT software.The bibliometric performance showed the number of publications and citations over time,scientific productivity and the geographic distribution of publications and research fields.The strategic diagram yielded 20 clusters and their relative importance in terms of centrality and density.The thematic evolution structure presented the most important themes and how it changes over time.Lastly,we presented the main challenges and future opportunities of big data in healthcare.

对当前引文分析研究中若干问题的思考

对引文分析的理论前提进行了再认识，讨论了引文分析的时效性、引文行为与ｃｏ－ｗｏｒｄ分析，并指出了我国引文分析研究中存在的问题。

Forestry big data platform by Knowledge Graph

Using the advantages of web crawlers in data collection and distributed storage technologies,we accessed to a wealth of forestry-related data.Combined with the mature big data technology at its present stage,Hadoop's distributed system was selected to solve the storage problem of massive forestry big data and the memory-based Spark computing framework to realize real-time and fast processing of data.The forestry data contains a wealth of information,and mining this information is of great significance for guiding the development of forestry.We conducts co-word and cluster analyses on the keywords of forestry data,extracts the rules hidden in the data,analyzes the research hotspots more accurately,grasps the evolution trend of subject topics,and plays an important role in promoting the research and development of subject areas.The co-word analysis and clustering algorithm have important practical significance for the topic structure,research hotspot or development trend in the field of forestry research.Distributed storage framework and parallel computing have greatly improved the performance of data mining algorithms.Therefore,the forestry big data mining system by big data technology has important practical significance for promoting the development of intelligent forestry.

Bibliometric analysis of subject trends and knowledge structures of gut microbiota

BACKGROUND Gut microbiota is an emerging field of research,with related research having breakthrough development in the past 15 years.Bibliometric analysis can be applied to analyze the evolutionary trends and emerging hotspots in this field.AIM To study the subject trends and knowledge structures of gut microbiota related research fields from 2004 to 2018.METHODS The literature data on gut microbiota were identified and downloaded from the PubMed database.Through biclustering analysis,strategic diagrams,and social network analysis diagrams,the main trend and knowledge structure of research fields concerning gut microbiota were analyzed to obtain and compare the research hotspots in each period.RESULTS According to the strategic coordinates and social relationship network map,Clostridium Infections/microbiology,Clostridium Infections/therapy,RNA,Ribosomal,16S/genetics,Microbiota/genetics,Microbiota/immunology,Dysbiosis/immunology,Infla-mmation/immunology,Fecal Microbiota Transplantation/methods,Fecal Microbiota Transplantation can be used as an emerging research hotspot in the past 5 years(2014-2018).CONCLUSION Some subjects were not yet fully studied according to the strategic coordinates;and the emerging hotspots in the social network map can be considered as directions of future research.

科技辅助第二语言教学研究趋势及其对国际中文教育的启示

In recent years,the enabling role of technology has been widely recognized in second language teaching and learning.Using a co-word analysis approach,this study aims to present the state-ofthe-art current literature in technology enhanced language learning.The analysis results show that most popular research themes from 2010 to 2020 are CMC,L2 writing,teacher education,L2 motivation,students’attitudes,SLA,L2 vocabulary learning,L2 reading,EFL,and L2 learners.Compared with these key themes,publications on technology enhanced teaching Chinese as a foreign language focus more on the investigation of the effectiveness of the use of latest technologies such as smart phones,virtual reality,intelligent tools,and gamification.Based on the findings of these investigations,the latest developments in these areas are synthesized and presented accordingly.In addition,newly-emerged key themes about the co-word analysis are also reported and their contributions to future investigations is briefly discussed.The implications for future research in technology enhanced teaching Chinese as a foreign language is also discussed.

Evolution Characteristics of the Information Literacy Education Policy for Chinese College Students

In order to cultivate information literacy among college students,the Chinese government has formulated a series of relevant policies as well as revised and adjusted the policy priorities along with the times.Guided by co-word and social network analysis,this study analyzes 170 policy texts that have been promulgated by the Chinese government from 1981 to 2020.Based on the clustering results of high-frequency keywords,this study explores the characteristics of policy evolution and its influencing factors from three dimensions:policy themes,contents of information literacy education,and the methods for cultivating information literacy education.Several suggestions have also been put forward in this article to improve the information literacy education policy for Chinese college students.

Content analysis of documents using neural networks: A study of Antarctic science research articles published in international journals

Content analysis of scientific papers emanating from Antarctic science research during the 25 years period （1980-- 2004） has been carried out using neural network based algorithm-CATPAC. A total of 10 942 research articles published in Science Citation Indexed （SCI） journals were used for the study. Normalized co-word matrix from 35 most-used significant words was used to study the semantic association between the words. Structural Equivalence blocks were constructed from these 35 most-used words. Four-block model solution was found to be optimum. The density table was dichotomized using the mean density of the table to derive the binary matrix, which was used to construct the network map. Network maps represent the thematic character of the blocks. The blocks showed preferred connection in establishing semantic relationship with the blocks, characterizing thematic composition of Antarctic science research. The analysis has provided an analytical framework for carrying out studies on the con- tent of scientific articles. The paper has shown the utility of co-word analysis in highlighting the important areas of research in Antarctic science.

Structure, Evolution and Hot Spots of Cooperation Innovation Knowledge Network

Based on the statistics analysis of cooperation innovation articles, the paper analyses the distributing characteristics of cooperation innovation research papers. The distribution, structure and evolution of cooperation innovation research are studied through the social network and co-word method, combined with the information visualization technology. This study is based on the papers in the SSCI database during 2000-2014. The analysis and statistics of papers reveal distribution characteristics of the subject, time, institutions, countries and areas. The statistics shows that the research perspective of cooperation innovation from business and economics. The time distribution presents that research of cooperation innovation attracts enormous attention and the research achievement is increasing. From the distribution of organizations, countries and areas, North America and Europe countries maintain the leading position in this research field. But institutions and universities of China and other Asian countries or areas are witnessed their outstanding achievements in cooperation innovation research. Combining the co-word network analysis method, the paper studies the structure and content of cooperation innovation knowledge network in five stages and makes the net spectrum, visually showing the hot spots at various periods. The top highly cited papers in all five stages are reviewed simultaneously;their research hot spots and evolution process are concluded. The study shows 11 subjects including strategic alliances, social networks, R&D cooperation, R&D, technology transfer, alliances, knowledge management, social capital, entrepreneurship, trust, biotechnology are always the central issues in last 15 years. The focus of research is from the relationship between alliance and technology innovation to networking and knowledge innovation and then to open innovation.

A Study on the Focuses and Fronts of International Second Language Acquisition Researches -Statistical Analysis of the Articles Published in Language Learning(2012-2016)

Keywords word frequency and co-word analysis are adopted in an attempt to to investigate the focuses and fronts of inter-national second language acquisition(SLA) researches by analyzing the key words in articles published in the internationally re-nowned SLA academic journal Language Learning from 2012 to 2016. It is found that the best researched topics in SLA are vocabu-lary acquisition, explicit knowledge, form-focused teaching, language use, and so on, among which learner's language attracts themost attention. In terms of research methods, they become more diversified and interdisciplinary, as empirical studies take a domi-nant position and experiments still play a leading role, displaying an interdisciplinary feature.

How did high temperature extremes in southern Xinjiang,China induce the repaid rise in jujube futures prices in the summer of 2021?

In the summer of 2021,southern Xinjiang,China,experienced a temporary period of high temperature extremes.Because of this weather event,jujube futures prices rose by more than 50%in a short time.To clarify the influence mechanism of these two events,we investigated the current status of jujube farming and collected investors’online comments.We analysed these comments specifically using textual analysis tools,such as co-word networks.Results showed that the concerns of investors about the reduction in jujube production triggered by high temperature extremes were the primary reason for the rapid rise in jujube futures prices.Especially in combination with the cultivation density of jujube and their adaptability to the growing environment,a new understanding can be obtained.That is to say,when a crop is excessively densely cultivated in a region and is highly sensitive to a meteorological variable anomaly at a certain growth stage,a less destructive local extreme weather event could induce severe panic among investors regarding production reduction and thus influence the normal changes in futures price.In response to the impact mechanisms revealed in this study,we proposed policy recommendations,such as strengthening the degree of crop damage disclosure and designing weather futures derivatives,to address similar situations in the future.This study not only fills the gap in the research on the impact paths of high temperature extremes on jujube futures prices but also has a reference value for securing the stability of futures prices of related agricultural products in the future.

Research on the evolutionary characteristics of evaluation policies of Chinese science and technology talents

Science and technology talent evaluation is an important part of the talent development system and mechanism,and the state's emphasis on science and technology talent evaluation is reflect-ed in the national policy.This paper takes 49 policy documents on science and technology tal-ent evaluation issued by the state from 1978 to 2022 as the object,and uses policy text analysis,word frequency analysis and co-word network analysis to interpret the content of the policies.These policy texts are divided into four stages.200 high-frequency words were extracted from the policies in each stage after word segmentation was made,and the co-word matrixes and co-word networks were constructed for each stage.The research draws the following conclu-sions:1)The content of Chinese science and technology talent evaluation policies is gradually becoming concrete,and the concept of science and technology talent evaluation is gradually clear;2)The policies have transitioned from"scientific and technological development"to"sci-entific and technological innovation";3)The distribution of policies with different strengths is uneven;4)The cooperation between all departments involved in policy formulation is not e-nough.

Discovering the relationship of disasters from big scholar and social media news datasets

The construction method for chains of disasters or events is still one of the core scientific questions in studying the common rules of disaster’s evolution.Especially when dealing with the complexity and diversity of disasters,it is critical to make a further investigation on reducing the dependency of prior knowledge and supporting the comprehensive chains of disasters.This paper tries to propose a novel approach,through collecting the big scholar and social news data with disasterrelated keywords,analysing the strength of their relationships with the co-word analysis method,and constructing a complex network of all defined disaster types,in order to finally intelligently extract the unique disaster chain of a specific disaster type.Google Scholar,Baidu Scholar and Sina News search engines are employed to acquire the needed data,and the respectively obtained disaster chains are compared with each other to show the robustness of our proposed approach.The achieved disaster chains are also compared with the ones concluded from existing research methods,and the very reasonable result is demonstrated.There is a great potential to apply this novel method in disaster management domain to find more secrets about disasters.

Analysis on the rules of acupoint combination in treatment of pseudobulbar palsy based on co-occurrence relationship

Objective:To explore the rules of acupoint combination in acupuncture treatment of post-stroke pseudobulbar palsy(PBP),based on acupuncture prescriptions retrieved from literature and using complex network analysis.Methods:The articles were searched from China National Knowledge Infrastructure(CNKI),Wanfang and VIP databases as the source of data.The eligible articles were selected in accordance with inclusion and exclusion criteria.The relevant data were extracted to set up the acupoint prescription database in acupuncture treatment of PBP.By using co-occurrence relationship in acupoint prescriptions,the core acupoints and the combination rules were analyzed in acupuncture treatment of PBP.Results:A total of 194 articles were eligible finally,with 202 acupoint prescriptions extracted.19 core acupoints were collected in total,i.e.Liánquán(廉泉CV23),Fēngchí(风池GB20),Bǎihuì(百会GV20),Jīnjīn(金津EX-HN12),Yùyè(玉液EX-HN13),Fēngfǔ(风府GV16),Yǎmén(哑门GV15),Shuǐgōu(水沟GV26),Nèiguān(内关PC6),Fēnglóng(丰隆ST40),Wángǔ(完骨GB12),Sānyīnjiāo(三阴交SP16),Yìfēng(翳风TE17),Tōnglǐ(通里HT5),Tàichōng(太冲LR3),Hégǔ(合谷LI4),Hǎiquán(海泉EX-HN11),Jùquán(聚泉EX-HN10)and Yìntáng(印堂EX-HN3).The core acupoint groups were CV23-GB20,EX-HN12-EX-HN13 and GV26-PC6-SP6.Acupoints were mostly selected from governor vessel.The methods of acupoint combination included the combination of distal and nearby points,and the combination of the acupoints located in the front and on the back.Conclusions:In treatment of PBP with acupuncture,biaoben(manifestation and root cause)theory is emphasized,the methods for dispelling wind,resolving phlegm,regaining consciousness,and opening orifices are recommended.Moreover,the attentions are paid on spirit regulation,holistic adjustment,and syndrome differentiation in treatment.

A comparative study on the development of academic librarianship research published in China and international journals from 2016 to 2020

This study investigates the top authors,the most frequent keywords in selected top Chinese and international journals in academic librarian ship,and emergent themes by conducting network and cluster analysis.The results suggest that LIS researchers in China's Mainland were less active in publishing articles in international journals during the period examined.Chinese researchers fo cused more on reading promotion and new technology implementation in libraries,while international researchers discuss communications among diverse disciplines more.Drawing international subject librarians’practices could be an approach to transform Chinese academic libraries to cope with the library crisis by playing a role as a bridge among scholars from various disciplines.