A Metric Approach to Hot Topics in Biomedicine via Keyword Co-occurrence

Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.Findings:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.Research limitations:All analyses use keywords,without any other forms.Practical implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical developments.Originality/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.

Keyword Co-occurrence Analysis of Research on Innovation Ecosystem Studies

The aim of the paper is to identify and explore leading thematic areas within the research field related to innovation ecosystem.Based on data from the Web of Science database,the keywords frequency and its co-occurrence frequency pair were analyzed,and the theory of mapping knowledge domains was used to visualize the keywords co-occurrence network in innovation ecosystem to make further research of the heated issues.The findings indicate that the research scope involved in innovation ecosystem research is broad,and research content focus on micro and macro levels.According to the results of keywords co-occurrence analysis of different stages,innovation,network,knowledge,strategy,open innovation,value creation are the most important issues to innovation ecosystem research,given their position and role in the research network.The paper generates the added value mainly from the point of view of theory development.

Binary Image Steganalysis Based on Distortion Level Co-Occurrence Matrix

In recent years,binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information security.In most state-of-the-art binary image steganographic schemes,they always find out the flippable pixels to minimize the embedding distortions.For this reason,the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial domain.However,the distortion maps can be calculated for cover and stego images and the difference between them is significant.In this paper,a novel binary image steganalytic scheme is proposed,which is based on distortion level co-occurrence matrix.The proposed scheme first generates the corresponding distortion maps for cover and stego images.Then the co-occurrence matrix is constructed on the distortion level maps to represent the features of cover and stego images.Finally,support vector machine,based on the gaussian kernel,is used to classify the features.Compared with the prior steganalytic methods,experimental results demonstrate that the proposed scheme can effectively detect stego images.

创伤性心脏骤停文献计量及可视化分析

目的了解国内外创伤性心脏骤停(traumatic cardiac arrest,TCA)的研究现状及研究趋势。方法检索2000年1月1日~2024年3月19日Web of Science(WOS)核心合集数据库、中国知网(CNKI)、万方数据知识服务平台发表的TCA相关文献,利用CiteSpace 6.3.R1软件进行文献计量图谱分析。结果最终纳入中文文献80篇,英文文献341篇,发文量总体呈逐年上升趋势;相关研究集中于国外发达国家,美国发文量居首位(29.91%),中国居第2位(9.38%)。相关核心研究团体已形成,中文以浙江大学医学院附属第二医院的夏森林发文最多,为3篇;英文以英国的Alqudah发文最多,为4篇;《中华急诊医学杂志》中文载文量最多,为7篇;Resuscitation英文载文量最多,为35篇。共得到6个中文、16个英文关键词聚类标签,6个突现关键词。TCA相关研究热点集中在其流行病学、病理生理学、预防和救治策略等方面。结论该领域国内外关注度逐渐上升,与国外相比,我国的TCA相关研究较少,研究主题较为局限。TCA患者结局及其相关影响因素和干预措施是目前该领域的研究热点。未来我国应继续致力于创伤复苏能力水平建设,加大该领域的科研投入和机构合作,改善患者结局。

近十年国外比较教育研究文献的知识图景——基于ProQuest Education Database 2013-2023年数据

研究以ProQuest Education Database为数据源搜集样本,使用Python软件对2013-2023年国外比较教育研究文献进行知识图景分析。对研究文献高频关键词、核心发文机构、关键词网络中心性以及年度突现词频等采用知识图谱可视化的方法呈现,以此清晰、直观地识别英文研究论文中比较教育领域高频研究主题关键词,从而确定国外比较教育研究领域在2013-2023年间的文献研究焦点与主题演变。通过分析发现,包含高等教育国际化、教师教育与国际大规模学业评价、可持续发展教育,以及后疫情时代教育复苏、教育数字化与教育公平相关的国际比较研究关注度日趋增长。未来我国比较教育学应紧跟时代发展,立足本国教育实情,加强微观教育实践领域的研究,同时也应增强教育理论研究并拓展多种方法综合运用。

基于知识图谱的高校党建研究热点与演变分析

基于2000—2022年1180篇CSSCI期刊文献,对我国高校党建的研究进行知识图谱探析。研究发现,新世纪以来我国高校党建的研究可划分为党对高校的领导、学生主体向度、内容向度、路径方法及新时代发展等五个序列;研究关注度持续增加,热点演化与党的重要会议与文件颁布紧密相关,但也存在研究主题关联度不高,未形成有效合力的问题。未来可进一步加强和完善新时代高校党建理论体系,借鉴多学科工具方法与理论资源,进一步拓展高校党建研究的深度与广度。

基于CiteSpace可视化分析的高校智慧教育空间研究进展与启示

存量时代下,高校教育空间随数字化教学模式的改变而逐步迭代升级,随之而来的校园教育空间智慧化建设也为教育设施的效能提升、情境预测提供了新的方法与工具。本文运用CiteSpace可视化工具,呈现近十年来国内外高校智慧教育空间的研究热点,总结其研究现状与发展趋势,归纳出高校智慧校园建设的四个阶段及智慧教育空间所呈现的低碳化、人本化、多元化、复合化的阶段特征,以期为后续校园教育空间的更新与建设提供参考。

我国科学数据中心评价的知识图谱分析

在大数据时代背景下,科学数据中心的蓬勃发展使其绩效评价逐渐成为研究热点。通过对国内近十年科学数据中心评价相关成果的系统梳理,为我国科学数据中心评价模型的深化研究提供理论依据和参考。运用科学知识图谱法,借助CiteSpace软件对2013-2023年期间CNKI的科学数据中心评价研究相关文献进行关键词共现分析。研究发现:研究演进上看,2015-2019年为高峰期,文献数量呈现爆发式增长;研究热点上看,可归纳为评价对象、评价领域、评价指标体系、绩效评估模式。经过对各个主题的深入分析,发现科学数据中心评价已经有一定程度的研究成果积累,然而,对于我国的科学数据中心体系而言,现有的评价体系在可比性和通用性方面存在一定的不足,这对科学数据中心的协调统一发展形成了阻碍。

Determining future high speed rail review topics through bibliometric analysis

As High Speed Rail(HSR)has proliferated globally,so has a related research field dedicated to exploring and addressing its unique issues.Yet,studies to understand and classify the HSR research domain are limited.This paper addresses the gap,using bibliometric analysis to identify future research areas and 20 candidate topics for literature review based on keyword analysis through VOSviewer.Article and review papers related to HSR published in the last 20 years(2003-2022)were retrieved from Scopus,and then analyzed to determine the split in knowledge between languages,the collaboration between countries and institutions,highly productive and cited journals,and research topics which have and have not been reviewed.Approximately 30%of the search results were published exclusively in Chinese,highlighting the importance of extending the evaluation to cover both languages.This is a novel aspect of the work,which has enabled the recognition of potential knowledge gaps.It is recommended that future reviews incorporate works in both languages,possibly through international collaboration.Institutions in China and other countries that are strong collaborators have been identified,as well as relevant,highly cited journals.

基于CiteSpace的空间句法研究热点 与趋势可视化分析

空间句法作为一种分析和解释城市与建筑空间布局及其对人类行为和社会动态的影响的理论和方法工具,已经引起了国际和国内学术界的广泛关注。研究基于中文核心(CNKI)和英文核心(WoS)数据库,覆盖了2003-2023年的相关核心文献。运用CiteSpace软件进行了关键词分析和知识图谱的绘制。结果表明:①空间句法作为研究领域在国际和国内层面均获得了持续增长的关注;②中英文数据库在空间句法研究上表现出既有共同点又有各自独特的发展路径和研究重点;③国内外在空间句法研究的未来发展方向上存在显著差异,这为双方提供了互相借鉴和学习,共同推动该领域的创新发展的机会。未来研究方向包括:①继续深化中英文数据库的比较研究;②加强国际与国内的研究合作,共享数据和成果,同时尊重各自的研究特色和研究方法。研究成果可为空间句法研究的深入扩展提供参考。

智慧水利领域研究热点的文献计量与可视化分析

为全面了解中国智慧水利领域发展状况,基于中国知网(CNKI)数据库,利用CiteSpace软件对2016—2023年的智慧水利领域研究文献进行了计量和可视化分析。通过对年发文量、期刊来源、高被引文献、主要作者、研究机构、关键词等要素进行统计分析,归纳总结了智慧水利领域研究知识基础和热点主题。在时空上看,智慧水利领域发文量具有前期慢、近期快的特点,整体发文量随时间变化呈指数型的增长趋势。结果表明:《水利信息化》是2016—2023年内刊发智慧水利领域文章最多的期刊,蒋云钟是该时间段内发表研究性文章最多的学者,《关于智慧水利的认识与思考》一文被引用次数最多,中国水利水电科学研究院是当前研究智慧水利领域最活跃、最广泛的科学研究机构,而数字孪生、大数据、数据底板等在智慧水利建设方面研究更为深入。最后,针对数字孪生技术在水利工程研究进行了具体分析,表明数字孪生技术是今后一段时间水利发展的前沿趋势。

基于CiteSpace的柴胡疏肝散文献研究可视化分析

目的:通过对柴胡疏肝散相关文献进行可视化分析,梳理柴胡疏肝散发展概况及研究热点。方法:检索中国知识资源总库(CNKI)、中国学术期刊数据库(万方数据)、中文科技期刊数据库(VIP)、中国生物医学文献数据库(CBM)2003年1月1日至2023年1月7日收录的柴胡疏肝散研究文献。通过NoteExpress合并去重,采用CiteSpace 6.1.R6软件对作者、机构、关键词绘制可视化图谱并进行解读。结果:纳入文献2177篇,发文量最多的作者是凌江红;各机构间合作较少;关键词分析提示研究内容主要集中在中西医联合治疗、动物实验等相关领域。结论:近20年柴胡疏肝散研究发文量整体呈上升趋势。基于柴胡疏肝散改善患者生活质量以及通过网络药理学研究柴胡疏肝散的用药规律可能是未来研究的热点与方向。

APPLICATION OF MAP AND FILE INFORMATIONVISUALIZATION SYSTEM TO COMPREHENSIVEDIVISION OF NATURAL DISASTERS- Takingthe ChangjiangValleg as an Example

ABSTRACT: This paper generalizes the makeup and forming dynamic mechanism of natural disaster systems, principles and methods of comprehensive division of natural disasters, as well as structure, function and up-build routes of map and file information visualization system (MFIVS). Taking the Changjiang(Yangtze) Valley as an example, on the basis of revealing up the integrated mechanism on the formations of its natural disasters and its distributing law, thereafter, the paper relies on the MFIVS technique, adopts two top-down and bottom-up approaches to study a comprehensive division of natural disasters. It is relatively objective and precise that the required division results include three natural disaster sections and nine natural disaster sub-sections, which can not only provide a scientific basis for utilizing natural resources and controlling natural disaster and environmental degradation, but also be illuminated to a concise, practical and effective technique on comprehensive division.

A comparison of mapping strategies from DDC to CLC

Purpose: This study aims to discuss the strategies for mapping from Dewey Decimal Classification(DDC) numbers to Chinese Library Classification(CLC) numbers based on co-occurrence mapping while minimizing manual intervention.Design/methodology/approach: Several statistical tables were created based on frequency counts of the mapping relations with samples of USMARC records,which contain both DDC and CLC numbers. A manual table was created through direct mapping. In order to find reasonable mapping strategies,the mapping results were compared from three aspects including the sample size,the choice between one-to-one and one-to-multiple mapping relations,and the role of a manual mapping table.Findings: Larger sample size provides more DDC numbers in the mapping table. The statistical table including one-to-multiple DDC-CLC relations provides a higher ratio of correct matches than that including only one-to-one relations. The manual mapping table cannot produce a better result than the statistical tables. Therefore,we should make full use of statistical mapping tables and avoid the time-consuming manual mapping as much as possible.Research limitations: All the sample sizes were small. We did not consider DDC editions in our study. One-to-multiple DDC-CLC relations in the records were collected in the mapping table,but how to select one appropriate CLC number in the matching process needs to be further studied.Practical implications: The ratio of correct matches based on the statistical mapping table came up to about 90% by CLC top-level classes and 76% by the second-level classes in our study. The statistical mapping table will be improved to realize the automatic classification of e-resources and shorten the cataloging cycle significantly.Originality/value: The mapping results were investigated from different aspects in order to find suitable mapping strategies from DDC to CLC while minimizing manual intervention.The findings have facilitated the establishment of DDC-CLC mapping system for practical applications.

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.

基于知识图谱的驾驶愤怒研究现状及热点可视化分析

为统计分析近年来国内外驾驶愤怒研究现状与热点,选取Web of Science(WOS)数据库1190篇相关论文以及中国知网(CNKI)数据库230篇相关论文作为数据源,借助文献计量学软件VoSviewer与CiteSpace生成知识图谱,并从载文量分布、作者与机构合作、发表期刊、关键词聚类与突现等方面,系统分析驾驶愤怒领域内的研究现状、热点与趋势等。结果表明:相关文献载文量不断上升,国内外学术界对驾驶愤怒领域关注度越来越高;国际驾驶愤怒领域的跨单位合作比国内更为广泛;驾驶愤怒相关量表、驾驶愤怒影响因素、愤怒与危险/攻击性驾驶行为关系、驾驶愤怒识别、驾驶愤怒干预为目前驾驶愤怒领域5大研究热点;愤怒状态下的驾驶绩效、驾驶愤怒检测系统以及基于交通工程视角的驾驶愤怒管控等方面是未来的研究趋势。

区域协同创新研究现状、热点与前沿分析

区域协同创新能够促进区域间创新要素流动和创新资源整合,是实现区域合作共赢的重要手段。文中运用CiteSpace和R语言工具,基于SSCI和CSSCI、北大中文核心引文索引数据库对区域协同创新领域相关文献进行可视化分析,探索区域协同创新领域的研究现状、研究热点、研究前沿及异同点。研究结果表明:较国际而言,国内区域协同创新研究起步较晚,发文量和研究学者数量均较少,但整体呈上升趋势。区域协同创新绩效和区域协同创新系统研究是国内、国际区域协同创新领域共同关注的内容,此外,国内还重点探究了产业协同创新研究,国际上则重点强调了区域绿色协同创新研究。未来国内区域协同创新领域应积极拓展区域协同创新绩效提升路径研究范围,强化区域绿色协同创新研究,重视区域协同创新政策研究。

基于文献计量的自动驾驶名词体系构建方法

作为新兴前沿交叉学科,自动驾驶领域名词亟须进行规范。文章使用VOSviewer软件作为工具,对Web of Science核心合集中1991—2021年自动驾驶领域的5087篇文献进行关键词计量与可视化呈现,并对自动驾驶领域的名词与科技前沿进行了分析。文章根据科技名词规范化工作原则,以关键词聚类图谱为基础,尝试构建自动驾驶名词框架,包括智能网联系统、智能驾驶信息和人机协同驾驶三个分支,并对名词框架体系进行了分析。文章的研究是名词审定工作流程中阶段性工作的一种创新尝试,以文献计量学方法为工具开展前沿交叉领域名词的规范化工作。

高质量发展背景下旅游创新驱动力组态路径——基于关键词数据的QCA分析

高质量发展是创新驱动式的发展,而旅游业的高质量发展更需要创新力量的驱动。本文研究对象是旅游创新驱动力及其驱动因素,目的是探究在旅游产业蓬勃发展过程中哪些领域是驱动旅游创新的源头,哪些领域更具有创新活力。本研究通过对以往10年旅游创新核心文献的知识图谱化处理,提取关键词数据指标作为充分条件,对选定案例进行了模糊集定性比较研究(fsQCA),得出了6条组态路径。经过对组态路径的解读分析,获得了基础创新、融合创新、协同创新、模式创新、资源创新、热点创新六个旅游创新驱动力构成因素,为旅游创新的学术探讨和具体实践提供了分析和参考依据。