CiteSpace中文手册

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CiteSpace中文手册

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5.2 打开地理可视化功能 ......................................................................................................... 41 5.3 相关参数设置 ..................................................................................................................... 41 5.4 结果的展示 ......................................................................................................................... 42 5.5 结果的编辑 ......................................................................................................................... 43 5.6 使用其他程式可视化 KML 文件 ........................................................................................ 45 6 Derwent 专利数据分析 ............................................................................................................. 47 6.1 登录 Derwent Innovations Index 数据库.

citespace使用教程

citespace使用教程CiteSpace是一种用于可视化分析科学文献的工具，它能够帮助研究人员发现文献之间的关联和趋势。

以下是使用CiteSpace的简单教程：1. 数据收集：首先，从主要的学术文献数据库（如Web of Science、Scopus等）中收集你感兴趣的文献数据。

可以根据关键词、作者、时间范围等进行检索，并将检索结果导出为文本文件（如BibTeX格式）。

2. 数据预处理：在使用CiteSpace之前，需要对文献数据进行预处理。

打开CiteSpace，单击"File"->"New"->"Create"，选择要分析的文献文件，并根据需要设置文献类型（如文章、会议论文等）和时间范围。

3. 数据导入：在CiteSpace中，选择"File"->"Import"，将预先处理的文献数据导入CiteSpace中进行分析。

4. 可视化图表：CiteSpace会根据文献数据生成各种可视化图表，以揭示文献之间的关联。

其中最常见的是共被引用网络图（Citation network），用来表示文献之间的引用关系。

另外，还可以生成时间分析图（Temporal analysis）和主题演化图（Evolutionary timeline）等。

5. 参数设置：在CiteSpace中，可以通过调整参数来优化可视化图表。

例如，可以设置阈值来过滤较少引用的文献，或者调整节点的大小和颜色来表示不同的特征。

6. 结果分析：在生成可视化图表后，要结合领域知识进行分析。

可以观察文献之间的联系和趋势，并探索可能的研究方向和前沿领域。

虽然CiteSpace可以提供很多有用的信息，但在分析结果时应该谨慎。

最好结合其他分析工具和领域专业知识，以更全面地理解文献之间的关系和趋势。

希望上述教程对你有帮助！。

信息计量学CiteSpace使用教程4

信息计量学CiteSpace使用教程4
5.数据处理窗口展示
数据处理窗口
数据处理窗口即展示了上节提到的Citespace支持的数据库类型。

在数据处理窗口，软件可以完成以下功能：
1.数据格式转换（最为常用）
2.数据获取：获取ADS、arXiv数据，属于citespace内置功能
3.数据处理（较为常用）：针对WoS数据，可以进行文件合并、文献去重、分隔符格式转换等。

具体内容如下图所示：
数据处理
1.整理数据（较少使用）：使用本功能要求会使用基本的SQL语句，具体界面如下。

整理数据
5. 基本操作流程
使用citespace的基本操作流程如框图所示，涉及到了数据采集、数据处理、导入软件、功能选择、可视化生成图谱和标签提取、图谱解读几个重要步骤。

基本操作流程
下面以文献共被引图谱分析来展示使用CiteSpace的方法：
5.1 前期工作
•获取数据
•数据转换（非WoS数据）
•以CNKI为例
•（1）新建两个文件夹“input”和“output”，将下载的文件放入“input”文件夹中
•（2）Data →Import→CNKI
•（3）Input directory选择“input”文件夹，Output directory选择“output”文件夹
•（4）点击format conversion，完成转换
•建立新工程；
•参数选择（功能面板选择cited reference）。

CiteSpace中文手册

CiteSpace中文手册CiteSpace是一款专业的学术数据分析软件，广泛应用于学术界的科研工作中。

本文将为您详细介绍CiteSpace的功能和使用方法，以帮助您更好地利用这一强大的工具进行学术研究。

一、CiteSpace概述CiteSpace是一款基于JAVA开发的学术数据分析软件，旨在帮助研究人员进行科学知识的可视化分析。

通过对各类学术文献的数据提取和处理，CiteSpace能够生成图表和网络图，揭示学术知识的发展动态和趋势。

二、CiteSpace的功能特点1. 数据导入与清洗：CiteSpace支持导入多种数据源，包括Web of Science和Scopus等主流学术数据库。

经过数据清洗，可以去除冗余信息，确保分析结果准确可靠。

2. 进行共词分析：CiteSpace能够识别学术文献中的共词关系，分析关键词之间的联系和频次分布。

这有助于发现研究领域的热点和前沿方向。

3. 构建共引网络：CiteSpace可以根据文献引用关系构建共引网络，揭示学术交流的密度和相关性。

通过对网络结构的分析，可以识别学术合作关系和学科交叉。

4. 提供科研指标：CiteSpace可以计算学术文献的引用频次、被引频次以及H指数等重要科研指标。

这些指标有助于评估学术成果的影响力和学者的学术影响力。

5. 可视化分析：CiteSpace支持多种图表和网络图的生成，可以直观地展示学术数据的分布和趋势，帮助研究人员进行深入分析和理解。

三、CiteSpace的使用方法1. 数据准备：首先，需要选择合适的数据源，如Web of Science或Scopus，并导出文献的元数据信息。

然后，通过CiteSpace的数据导入功能将数据加载到软件中进行处理。

2. 数据清洗：在导入数据后，需要进行数据清洗操作，去除重复记录和不完整的数据。

这可以确保后续分析的准确性和可靠性。

3. 分析设置：在进行CiteSpace分析之前，可以根据研究需求对分析参数进行设置，如时间跨度、分析深度等。

CiteSpace入门教程

CiteSpace入门教程在科研工作中，我们常常需要面对海量的文献，如何在这些文献当中找出值得精读、细读的关键文献，挖掘学科前沿，找到研究热点就成为了开展研究之前首先需要解决的问题。

CiteSpace作为一款优秀的文献计量学软件，能够将文献之间的关系以科学知识图谱的方式可视化的展现在操作者面前，既能帮助我们梳理过去的研究轨迹，也能使得我们对未来的研究前景有一个大概的认识。

CiteSpace 又翻译为“引文空间”，是一款着眼于分析科学分析中蕴含的潜在知识，是在科学计量学、数据可视化背景下逐渐发展起来的引文可视化分析软件。

由于是通过可视化的手段来呈现科学知识的结构、规律和分布情况，因此也将通过此类方法分析得到的可视化图形称为“科学知识图谱”。

摘自李杰.CiteSpace中文版指南正如科学计量学界的权威专家刘则渊教授对CiteSpace知识图谱形态的概括一样，“一图展春秋，一览无余；一图胜万言，一目了然”。

近年来，使用CiteSpace开展的研究、发表的论文呈现不断上升的趋势。

根据中国知网的统计，2023年相关论文已经达到388篇；到2023年预测将达到423篇。

使用CiteSpace开展的研究、发表的论文数目变化情况在如此多同质化的文章面前，我们应当如何做好自己的研究才能够不落入俗套，进而脱颖而出呢？我认为，在深入的把握CiteSpace的原理的基础上，熟稔相关操作背后的含义，对CiteSpace软件的应用达到游刃有余，这样才能知道自己的研究需要什么，做到“知己”。

同时了解相关文章的研究套路，清晰他们的研究内容和研究思路，取其精华，规避其错误，做到“知彼”。

下面根据我个人的一些学习的体会和实际使用的情况对CiteSpace使用过程来跟大家做一个基础性的介绍。

使用CiteSpace需要先安装JAVA 8，安装教程参考进入下一个界面，提醒使用者在使用这个软件开展研究的发表论文的时候，别忘了把软件开发者的论文引用上，不同意就用不了，那我们当然选择同意。

CiteSpace学习指南

CiteSpace学习指南1. CiteSpace基础CiteSpace全球使用的时间和空间特征被引分布：CiteSpace科技文本挖掘及可视化CiteSpace基础001：下载及安装CiteSpace基础002：软件原理CiteSpace基础003：最新安装视频CiteSpace基础004：不同版本使用说明CiteSpace基础005：知识图谱理论与实践CiteSpace：界定一个研究领域的学术格局CiteSpace理论基础与技术CiteSpace软件界面与功能CiteSpace对CNKI数据的分析CiteSpace对CSSCI数据的分析CiteSpace对Web of Science数据的分析CiteSpace对RSCI俄罗斯科学索引数据分析CiteSpace引文网络主路径分析CiteSpace对结构变异的分析CiteSpace的设计和分析原理CiteSpace的分析流程CiteSpace中Pathfinder的作用CiteSpace可视化案例视频Carrot对CiteSpace施引文献的聚类CiteSpace中文指南（最新版）2.CiteSpace可视化设计CiteSpace视图001：时区视图CiteSpace视图002：网络视图CiteSpace视图003：网络叠加图CiteSpace视图004：期刊叠加视图CiteSpace视图005：时间线视图CiteSpace视图006：主题配色3.CiteSpace案例图案例001：CiteSpace最新案例图案例002：CiteSpace最新案例图案例003：CiteSpace最新案例图案例004：CiteSpace最新案例图案例005：CiteSpace最新案例图案例006：CiteSpace最新案例图案例007：CiteSpace最新案例图案例008：CiteSpace最新案例图案例009：CiteSpace最新案例图案例010：CiteSpace最新案例图案例011：CiteSpace最新案例图案例012：CiteSpace最新案例图案例013：CiteSpace最新案例图案例014：CiteSpace最新案例图案例015：CiteSpace最新案例图案例016：CiteSpace最新案例图（主题图）案例017：CiteSpace最新案例图案例018：CiteSpace最新案例图案例019：CiteSpace最新案例图4. CiteSpace案例论文目录CiteSpace实践与应用：2021(1), 1-100CiteSpace实践与应用：2021(2), 101-200CiteSpace实践与应用：2021(3), 201-300CiteSpace实践与应用：2021(4), 301-400CiteSpace实践与应用：2021(5), 401-500CiteSpace实践与应用：2021(6), 501-545CiteSpace实践与应用：2020学位论文CiteSpace实践与应用：2014-2019学位论文CiteSpace实践与应用：10篇CiteSpace知识图谱博士论文CiteSpace实践与应用：10篇情报科学知识图谱学位论文CiteSpace实践与应用：14篇医学科学知识图谱博士论文CiteSpace实践与应用：10篇教育科学知识图谱学位论文CiteSpace实践与应用：10篇体育科学知识图谱学位论文CiteSpace实践与应用：图谱案例著作CiteSpace实践与应用：图谱案例论文5. CiteSpace问题问题001：CiteSpace论文问题问题002：CiteSpace论文问题问题003：CiteSpace论文问题CiteSpace问答001：常见问题CiteSpace问答002：分析中的异常要自己检查和完善CiteSpace问答003：关于国家或地区合作和关键词分析解决CiteSpace与VOSviewer软件字体太小6. 科学知识图谱基础基础知识001：文献共被引分析基础知识002：科研合作网络分析基础知识003：研究主题分析基础知识004：地理可视化基础知识005：科学计量与知识图谱免费指南基础知识006：科学知识图谱典型案例视频基础知识007：认识三计学基础知识008：数据库与数据采集基础知识009：科学知识图谱理论、方法与实践谁最早提出“文献计量学”这个词？文献计量学指标应用的四个群体简介科学计量学科学计量学与情报学的天然联系7. 科学知识图谱基础视频视频001：CiteSpace视频视频002：BibExcel视频视频003：VOSviewer视频视频004：SCI2视频视频005：R-Bibliometrix视频视频006：SCIMAT 视频视频007：文献计量中的基础概念视频008：不同领域的Bibliometrics 视频009：Nature 150年视频010：合作网络可视化。

CiteSpace操作指南

CiteSpace操作指南The CiteSpace ManualVersion 0.96Chaomei ChenCollege of Computing and InformaticsDrexel UniversityHow to cite:Chen, Chaomei (2014) The CiteSpace Manual. /doc/98eefc8258fb770bf68a5543.html /~cchen/citespace/CiteSpaceManual.pdf Contents1How can I find the latest version of the CiteSpace Manual? (5)2What can I use CiteSpace for? (5)2.1What if I have Questions (7)2.2How should I cite CiteSpace? (7)2.3Where are the Users of CiteSpace? (8)3Requirements to Run CiteSpace (10)3.1Java Runtime (JRE) (10)3.2How do I check whether Java is on my computer? (10)3.3Do I have a 32-bit or 64-bit Computer? (12)4How to Install and Configure CiteSpace (12)4.1Where Can I download CiteSpace from the Web? (12)4.2What is the maximum number of records that I can handle with CiteSpace? (13)4.3How to configure the memory allocation for CiteSpace? (13)4.4How to uninstall CiteSpace (14)4.5On Mac or Unix-based Systems (15)5Get Started with CiteSpace (19)5.1Try it with a demonstrative dataset (19)5.1.1The Demo Project (20)5.1.2Clustering (23)5.1.3Generate Cluster Labels (25)5.1.4Where are the major areas of research based on the input dataset? (27)5.1.5How are these major areas connected? (28)5.1.6Where are the most active areas? (28)5.1.7What is each major area about? Which/where are the key papers for a given area?365.1.8Timeline View (38)5.2Try it with a dataset of your own (39)5.2.1Collecting Data (39)5.2.2Working with a CiteSpace Project (43)5.2.3Data Sources in Chinese (44)5.2.4How to handle search results containing irrelevant topics (45)6Configure a CiteSpace Run (47)6.1Time Slicing (47)6.3Configure the Networks (48)6.3.1Bibliographic Coupling (49)6.4Node Selection Criteria (49)6.4.1Do I have the right network? (50)6.5Pruning, or Link Reduction (50)6.6Visualization (51)7Interacting with CiteSpace (51)7.1How to Show or Hide Link Strengths (51)7.2Adding a Persistent Label to a Node (52)7.3Using Aliases to Merge Nodes (53)7.4How to Exclude a Node from the Network (55)7.5How to Use the Fisheye View Slider (55)7.6How to Configure When to Calculate Centrality Scores Automatically (56) 7.7How to Save the Visualization as a PNG File (57)8Additional Functions (58)8.1Menu: Data (58)8.1.1CiteSpace Built-in Database (58)8.1.2Utility Functions for the Web of Science Format (61)8.1.3PubMed (62)8.2Menu: Network (64)8.2.1Batch Export to Pajek .net Files (64)8.3Menu: Geographical (64)8.3.1Generate Google Earth Maps (64)8.4Menu: Overlay Maps (67)8.4.1Add an Overlay (68)8.4.2Further Reading and Terms of Use (70)8.5Menu: Text (70)8.5.1Concept Trees and Predicate Trees (70)8.5.2List Terms by Clumping Properties (73)8.5.3Latent Semantic Analysis (74)9Selected Examples (75)10Metrics and Indicators (77)10.1Information Theoretic (77)10.2Structural (77)10.2.1Betweenness Centrality (77)10.2.2Modularity (77)10.2.3Silhouette (77)10.3Temporal (77)10.3.1Burstness (77)10.4Combined (77)10.4.1Sigma (77)10.5Cluster Labeling (78)10.5.1Term Frequency by Inversed Document Frequency (78)10.5.2Log-Likelihood Ratio (78)10.5.3Mutual Information (78)11References (78)1How can I find the latest version of the CiteSpace Manual?The latest version of the CiteSpace Manual is always at the following location:/doc/98eefc8258fb770bf68a5543.html /~cchen/citespace/CiteSpaceManual.pdfYou can also access the manual from CiteSpace: Help ?View the CiteSpace Manual (PDF). It will open up the PDF file in a new browser window.Figure 1. The latest version of the CiteSpace Manual is accessible from CiteSpace itself.2What can I use CiteSpace for?CiteSpace is designed to answer questions about a knowledge domain, which is a broadly defined concept that covers a scientific field, a research area, or a scientific discipline. A knowledge domain is typically represented by a set of bibliographic records of relevant publications. It is your responsibility to prepare the most appropriate and representative dataset that contains adequate information to answer your questions.CiteSpace is designed to make it easy for you to answer questions about the structure and dynamics of a knowledge domain. Here are some typical questions:What are the major areas of research based on the input datasetHow are these major areas connected, i.e. through which specific articlesWhere are the most active areasWhat is each major area about Which/where are the key papers for a given areaAre there critical transitions in the history of the development of the field Where are the ‘turning points’The design of CiteSpace is inspired by Thomas Kuhn’s structure of scientific revolutions. The central idea is that centers of research focus change over time, sometime incrementally and other times drastically. The development of science can be traced by studying their footprints revealed by scholarly publications.Members of the contemporary scientific community make their contributions. Their contributions form a dynamic and self-organizing system of knowledge. The system contains consensus, disputes, uncertainties, hypotheses, mysteries, unsolved problems, and unanswered questions. It is not enough to study a single school of thought. In fact, a better understanding of a specific topic often relies on an understanding of how it is related to other topics.The foundation of the CiteSpace is network analysis and visualization. Through network modeling and visualization, you can explore the intellectual landscape of a knowledge domain and discern what questions researchers have been trying to answer and what methods and tools they have developed to reach their goals.This is not a simple task. Rather it is often conceptually demanding and complex. If you are about to write a novel, the word processor or a text editor can make the task easier, but it cannot help you to create the plot or enrich the character of your hero. Similarly, and probably to a greater extent, CiteSpace can generate X-ray photos of a knowledge domain, but to interpret what these X-ray photos mean, you need to have some knowledge of various elements involved. The role of CiteSpace is to shift some of the traditionally labor-some burdens to computer algorithms and interactive visualizations so that you can concentrate on what human users are most good at in problem solving and truth finding. However, it is probably easier to generate some mysterious looking visualizations with CiteSpace than to fully understand what these visualizations tell you and who may benefit from such findings.Figure 2. Hierarchically organized functions of CiteSpace, for example, GUI ?Pruning ?Pathfinder: true.2.1What if I have QuestionsIf you have a question regarding the use of CiteSpace, you should first check the manual whether your question is answered in the manual. You can do a simple search through the PDF file to find out.If the manual does not get you anywhere, you can ask your questions on the Facebook page of CiteSpace:https:///doc/98eefc8258fb770bf68a5543.html /pages/CiteSpace/276625072366558You can also post questions to my blog on sciencenet:/doc/98eefc8258fb770bf68a5543.html /home.php?mod=space&uid=496649Please refrain from sending me emails because you will have a much better chance to get my response from either the Facebook or the sciencenet blog.Generally speaking, thoughtful questions get answered quickly. Questions that you may be able to figure out the answer for yourself if you think a little bit more about it would have a lower priority in the answering queue; it is quite possible that some of them never get answered.2.2How should I cite CiteSpace?The following three publications represent the core ideas of CiteSpace.The 2004 PNAS paper is the initial publication on CiteSpace (Chen 2004). In hindsight, it could have been named CiteSpace I. The 19-page 2006 JASIST paper gives the most thorough and in-depth description of CiteSpace II’s key functions (C. M. Chen, 2006), plus a follow-up study of domain experts identified in the visualizations. The 2010 JASIST paper is even longer with 24 pages (C. Chen, Ibekwe-SanJuan, & Hou, 2010), which is the third of the trilogy. It describes technical details on how cluster labels are selected and how each of the three selection algorithms in comparison with labels chosen by domain experts.ReferenceCitations(Google Scholar)800 Chen, C. (2006). "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature." Journal of the AmericanSociety for Information Science and Technology 57(3): 359-377.394 Chen , C. (2004). "Searching for intellectual turning points: Progressive Knowledge Domain Visualization." Proc. Natl. Acad. Sci. USA101(Suppl.): 5303-5310.157 Chen, C., et al. (2010). "The structure and dynamics of co-citation clusters:A multiple-perspective co-citation analysis." Journal of the AmericanSociety for Information Science and Technology 61(7): 1386-1409.The most recent case study of a topic outside the realm of information science and scientometrics is a scienometric study of regenerative medicine (C. Chen, Hu, Liu, & Tseng, 2012). Chen, C., et al. (2012). "Emerging trends in regenerative medicine: A scientometric analysis in CiteSpace."Expert Opinions on Biological Therapy 12(5): 593-608.2.3Where are the Users of CiteSpace?In terms of the cities where CiteSpace were used, China, the United States, and Europe are prominent. Brazil, Turkey, and Spain also have many cities on the chart.Figure 3. Cities with users of CiteSpace between August 2013 and March 2014 are shown on the map. The colors of markers depict the level of user intensity: green (1-10), yellow (10-100), red (100-1000), and the large red water dropshaped marker (1000+).Figure 4. The use of CiteSpace in China (August 2013 – March 2014).Figure 5. The use of CiteSpace in the United States (August 2013 – March 2014).Figure 6. The use of CiteSpace in Europe (August 2013 – March 2014).3Requirements to Run CiteSpace3.1Java Runtime (JRE)CiteSpace is written in Java. It is a Java application. You should be able to run it on a computer that supports Java, including Windows or Mac.CiteSpace is currently optimized for Windows 64-bit Java 7 (i.e. Java 1.7).To run a Java application on your computer, you need to have Java Runtime (JRE) installed on your computer.3.2How do I check whether Java is on my computer?Figure 7. Select Control Panel.Figure 8. Click into the Programs category to find the Java control panel.Figure 9. Locate the Java control panel.Figure 10. Java Control Panel. Choose the Java tab and press the View button to see more detail.Figure 11. Java Runtime 1.7 is installed.3.3Do I have a 32-bit or 64-bit Computer?You need to find out whether your computer has a 32-bit or a 64-bit operating system.Go to Control Panel ?System and Security ?System. You will see various details about your computer. Under the System type, you will see whether you have a 32-bit or a 64-bit operating system.Follow the link below for further instructions on how to install Java:/doc/98eefc8258fb770bf68a5543.html /en/download/help/index_installing.xmlOnce you have Java Runtime setup on your computer, you can proceed to install CiteSpace.4How to Install and Configure CiteSpaceCiteSpace is provided as a zip file for 64-bit and 32-bit computers. For Mac users, you need to download the 64-bit version.4.1Where Can I download CiteSpace from the Web?You can download the latest version of CiteSpace from the following website:/doc/98eefc8258fb770bf68a5543.html /~cchen/citespace/download.htmlFigure 12.The download page of CiteSpace.After you download the zip file to your computer, unpack the zip file to a folder of your choice.Figure 13. CiteSpace is unpacked to the D drive on a computer.Now you can start CiteSpace by double clicking on the StartCiteSpace file.If you need to modify the amount memory allocated for CiteSpace (more precisely for Java Virtual Machine on which CiteSpace to be running), you can edit StartCiteSpace as a plain text file with any text editor.4.2What is the maximum number of records that I can handle with CiteSpace?This question needs to be answered at two levels: the number of records processed by CiteSpace and the number of nodes visualized, i.e. you can see and interact with them in CiteSpace. The first number is the total number of records in your downloaded dataset. CiteSpace reads through each record in your download files.The second number is determined by the selection criteria you specify and by the amount of memory, i.e. RAM, available on your computer. The more RAM you can make available for CiteSpace, the larger sized network you can visualize with a faster response rate.The speed of processing is also affected by a few computationally expensive algorithms such as Pathfinder network scaling and cluster labeling. Empirically, the best options for Pathfinder network scaling would be 50~500 nodes per slice. With faster computers or if you can wait for a bit longer, you can raise the number accordingly.The completion time of cluster labeling is related to the size of your dataset. If the entire timespan of your dataset is 100 years but you will only need to consider the most recent 10 years, it will be a good idea to carve out a much smaller dataset as long as it covers the 10 years of interest. It will reduce the processing time considerably.4.3How to configure the memory allocation for CiteSpace?The performance of CiteSpace is influenced by the amount of memory accessible to the Java Virtual Machine (JVM) on which CiteSpace is running. To analyze a large amount of records, you should consider allocating as much as memory for CiteSpace to use.You can modify the StartCiteSpace.cmd file to optimize the setting. More specifically, modify line 14 in the file. For example, -Xmx2g means that CiteSpace may get a maximum of 2GB of RAM to work with. Save the file after making any changes. And restart CiteSpace.Figure 14. Configure the memory for Java in line 14.4.4How to uninstall CiteSpaceYou can use the following steps to remove cached copies of CiteSpace from your computer.Figure 15. In a Command Prompt window, type javaws –viewer.When you see a list of cached copies of CiteSpace in the Java Cache Viewer, select the items that you want to remove and then click on the button with a red cross.Figure 16. Select a cached copy of CiteSpace and remove the item.4.5On Mac or Unix-based SystemsThe following example shows you the basic steps to get started with CiteSpace on a Mac. First, go to the CiteSpace homepage in a browser such as Chrome and download the latest 64-bit version.Figure 17. On a Mac, go to the CiteSpace home page in a browser such as Chrome and download the latest 64-bit version. Once the download is completed, follow the option “Show in Finder.” It will take you to a list of files downloaded to your Mac. The most recent file should be the zip file for CiteSpace.Figure 18. Choose “Show in Finder.”Figure 19. The downloaded zip file is shown in your Finder.Double-click on the zip file to unzip the file to a folder in the current folder.Figure 20. The zip file is unzipped to a new folder on the list.Figure 21. The new folder contains CiteSpaceII.jar and a lib folder.The simplest way to get started with CiteSpace is to open the CiteSpaceII.jar by clicking on it while holding the “Control” key on Mac. Select Open from the pop-up menu.Figure 22. Click on the CiteSpaceII.jar while holding the “Control” key and select “Open.”Due to the Java security settings, you will see a dialog box with two options for Open or Cancel.Choose Open to proceed. It will not harm your computer.Figure 23. Choose “Open” from the dialog box to proceed.After you choose Open, CiteSpace is getting started on Mac. You will see its opening page asfollows. Choose “Agree” to continue.Figure 24. CiteSpace is now started on Mac.Figure 25. Screenshots of running the Demo project of CiteSpace on Mac.It is a good idea to get familiar with the basic functions of CiteSpace by going through the Demo project on terrorism, which is included in the zip file.If you want to configure various Java Virtual Machine parameters in more detail than what is shown in the above example, you may generate a bash file for your Mac as follows.The Mac equivalent of the StartCiteSpace.cmd would be a bash file, which should have a file extension of .sh and should be executable. Let’s name the file as StartCiteSpace.sh to be consistent.1.The content of the StartCiteSpace.sh file should have the following two lines:#!/bin/bashjava -Xms1g -Xmx4g -Xss5m -jar CiteSpaceIII.jar2.The following instruction turns the StartCiteSpace.sh file to an executable file:chmod +x StartCiteSpace.sh3.To invoke the executable file, simply type its name or double click on it.StartCiteSpace5Get Started with CiteSpace5.1Try it with a demonstrative datasetWhen you installed CiteSpace for the first time, a demonstrative dataset on terrorism research is setup for you to play with and get familiar with the major analytic functions in CiteSpace. If you have never used CiteSpace before, I strongly recommend you to start with this demo dataset.To launch CiteSpace, double click on the StartCiteSpace.cmd file. You will see a command prompt window first. This window will also display various information on the status and any errors.Figure 26. The command prompt window.You will see another window of “About CiteSpace” – it displays system information of your computer, including the Java version. To proceed, you need to click on the Agree button. CiteSpace may collect user driven events for research purposes.。

CiteSpace介绍与使用

CiteSpace介绍与使用1. What is CiteSpace?CiteSpace:引文空间是一款眼着与分析科学分析中蕴含的潜在知识，是在科学计量学、数据可视化背景下逐渐发展起来的一款引文可视化分析软件。

由于是通过可视化的手段来呈现科学知识的结构、规律和分布情况，因此也将通过此类方法分析得到的可视化图形称为“科学知识图谱”。

（摘自李杰.CiteSpace中文版指南）对于我个人而言，学习使用CiteSpace的目的是快速了解所研究方向的“论文图谱”，被引用数是论文是否优质的重要标志，故通过论文引用图谱，我可以知道哪些论文是优质的，哪些论文是具有开创性的，并且具有开创性质的论文一般不会那么复杂，较容易理解，为日后学习打基础。

2.How to use CiteSpace?在本节我将以自己研究方向为例，构建论文引用图谱首先点击StartCiteSpace.bat ，打开CiteSpace。

然后就可以看到如下较为'原生态’的界面。

CiteSpace自身带了一个example，就是Terrorism。

我现在需要新建一个Project，来建立自己的主题项目。

先点上图的1，“New”，进入下图界面。

上图的2，需要分别建立两个文件夹，一个空文件是Project，另一个Data。

这里简要说一下这两个文件夹的作用，Project文件夹是用来保存分析的结果，不需要添加其他内容。

Data文件是存放将要被分析的数据，这个需要我们去检索，下载，然后放到这个文件夹，具体找什么如下图。

首先找 cross modal 主题 2010-2017年的所有论文。

在上两个图可以知，检索结果有3208篇论文，我们现在要做的是将所有记录信息下载下来，由于Web of Science 限制每次只能下载500条记录，故要多次下载，每次变化的是记录范围1至500,501至1000,1001至1500…，将每次下载的文件改名为download_xxx.txt(这是因为CiteSpace只识别以download_为前缀的文件名）下载后的数据文件：有了数据我就可以使用CiteSpace进行引用分析了，还记得最初的那个“原生态”的界面吗？就是它选择年份，2010-2017，时间间隔为1年。

CiteSpace使用手册

The CiteSpace ManualVersion 1.01Chaomei ChenCollege of Computing and InformaticsDrexel UniversityHow to cite:Chen, Chaomei (2014) The CiteSpace Manual. /~cchen/citespace/CiteSpaceManual.pdfContents1How can I find the latest version of the CiteSpace Manual? (5)2What can I use CiteSpace for? (5)2.1What if I have Questions (7)2.2How should I cite CiteSpace? (7)2.3Where are the Users of CiteSpace? (8)3Requirements to Run CiteSpace (10)3.1Java Runtime (JRE) (10)3.2How do I check whether Java is on my computer? (10)3.3Do I have a 32-bit or 64-bit Computer? (12)4How to Install and Configure CiteSpace (12)4.1Where Can I download CiteSpace from the Web? (12)4.2What is the maximum number of records that I can handle with CiteSpace? (13)4.3How to configure the memory allocation for CiteSpace? (13)4.4How to uninstall CiteSpace (14)4.5On Mac or Unix-based Systems (15)5Get Started with CiteSpace (19)5.1Try it with a demonstrative dataset (19)5.1.1The Demo Project (20)5.1.2Clustering (23)5.1.3Generate Cluster Labels (25)5.1.4Where are the major areas of research based on the input dataset? (27)5.1.5How are these major areas connected? (28)5.1.6Where are the most active areas? (28)5.1.7What is each major area about? Which/where are the key papers for a given area?365.1.8Timeline View (38)5.2Try it with a dataset of your own (39)5.2.1Collecting Data (39)5.2.2Working with a CiteSpace Project (43)5.2.3Data Sources in Chinese (44)5.2.4How to handle search results containing irrelevant topics (45)6Configure a CiteSpace Run (47)6.1Time Slicing (47)6.3Configure the Networks (48)6.3.1Bibliographic Coupling (49)6.4Node Selection Criteria (49)6.4.1Do I have the right network? (50)6.5Pruning, or Link Reduction (50)6.6Visualization (51)7Interacting with CiteSpace (51)7.1How to Show or Hide Link Strengths (51)7.2Adding a Persistent Label to a Node (52)7.3Using Aliases to Merge Nodes (53)7.4How to Exclude a Node from the Network (55)7.5How to Use the Fisheye View Slider (55)7.6How to Configure When to Calculate Centrality Scores Automatically (56)7.7How to Save the Visualization as a PNG File (57)7.8Filters: Match Records with Pubmed (58)8Additional Functions (62)8.1Menu: Data (62)8.1.1CiteSpace Built-in Database (62)8.1.2Utility Functions for the Web of Science Format (65)8.1.3Scopus (66)8.1.4PubMed (67)8.2Menu: Network (69)8.2.1Batch Export to Pajek .net Files (69)8.3Menu: Geographical (69)8.3.1Generate Google Earth Maps (69)8.4Menu: Overlay Maps (72)8.4.1Add an Overlay (73)8.4.2Further Reading and Terms of Use (75)8.5Menu: Text (75)8.5.1Concept Trees and Predicate Trees (75)8.5.2List Terms by Clumping Properties (78)8.5.3Latent Semantic Analysis (79)9Selected Examples (80)10.1Information Theoretic (82)10.1.1Information Entropy (82)10.2Structural (82)10.2.1Betweenness Centrality (82)10.2.2Modularity (82)10.2.3Silhouette (82)10.3Temporal (82)10.3.1Burstness (82)10.4Combined (82)10.4.1Sigma (82)10.5Cluster Labeling (83)10.5.1Term Frequency by Inversed Document Frequency (83)10.5.2Log-Likelihood Ratio (83)10.5.3Mutual Information (83)11References (83)1How can I find the latest version of the CiteSpace Manual?The latest version of the CiteSpace Manual is always at the following location:/~cchen/citespace/CiteSpaceManual.pdfYou can also access the manual from CiteSpace: Help ►View the CiteSpace Manual (PDF). It will open up the PDF file in a new browser window.Figure 1. The latest version of the CiteSpace Manual is accessible from CiteSpace itself.2What can I use CiteSpace for?CiteSpace is designed to answer questions about a knowledge domain, which is a broadly defined concept that covers a scientific field, a research area, or a scientific discipline. A knowledge domain is typically represented by a set of bibliographic records of relevant publications. It is your responsibility to prepare the most appropriate and representative dataset that contains adequate information to answer your questions.CiteSpace is designed to make it easy for you to answer questions about the structure and dynamics of a knowledge domain. Here are some typical questions:•What are the major areas of research based on the input dataset?•How are these major areas connected, i.e. through which specific articles?•Where are the most active areas?•What is each major area about? Which/where are the key papers for a given area?•Are there critical transitions in the history of the development of the field? Where are the ‘turning points’?The design of CiteSpace is inspired by Thomas Kuhn’s structure of scientific revolutions. The central idea is that centers of research focus change over time, sometime incrementally and other times drastically. The development of science can be traced by studying their footprints revealed by scholarly publications.Members of the contemporary scientific community make their contributions. Their contributions form a dynamic and self-organizing system of knowledge. The system contains consensus, disputes, uncertainties, hypotheses, mysteries, unsolved problems, and unanswered questions. It is not enough to study a single school of thought. In fact, a better understanding of a specific topic often relies on an understanding of how it is related to other topics.The foundation of the CiteSpace is network analysis and visualization. Through network modeling and visualization, you can explore the intellectual landscape of a knowledge domain and discern what questions researchers have been trying to answer and what methods and tools they have developed to reach their goals.This is not a simple task. Rather it is often conceptually demanding and complex. If you are about to write a novel, the word processor or a text editor can make the task easier, but it cannot help you to create the plot or enrich the character of your hero. Similarly, and probably to a greater extent, CiteSpace can generate X-ray photos of a knowledge domain, but to interpret what these X-ray photos mean, you need to have some knowledge of various elements involved. The role of CiteSpace is to shift some of the traditionally labor-some burdens to computer algorithms and interactive visualizations so that you can concentrate on what human users are most good at in problem solving and truth finding. However, it is probably easier to generate some mysterious looking visualizations with CiteSpace than to fully understand what these visualizations tell you and who may benefit from such findings.Figure 2. Hierarchically organized functions of CiteSpace, for example, GUI ►Pruning ►Pathfinder: true.2.1What if I have QuestionsIf you have a question regarding the use of CiteSpace, you should first check the manual whether your question is answered in the manual. You can do a simple search through the PDF file to find out.If the manual does not get you anywhere, you can ask your questions on the Facebook page of CiteSpace:https:///pages/CiteSpace/276625072366558You can also post questions to my blog on sciencenet:/home.php?mod=space&uid=496649Please refrain from sending me emails because you will have a much better chance to get my response from either the Facebook or the sciencenet blog.Generally speaking, thoughtful questions get answered quickly. Questions that you may be able to figure out the answer for yourself if you think a little bit more about it would have a lower priority in the answering queue; it is quite possible that some of them never get answered.2.2How should I cite CiteSpace?The following three publications represent the core ideas of CiteSpace.The 2004 PNAS paper is the initial publication on CiteSpace (Chen 2004). In hindsight, it could have been named CiteSpace I. The 19-page 2006 JASIST paper gives the most thorough and in-depth description of CiteSpace II’s key functions (C. M. Chen, 2006), plus a follow-up study of domain experts identified in the visualizations. The 2010 JASIST paper is even longer with 24 pages (C. Chen, Ibekwe-SanJuan, & Hou, 2010), which is the third of the trilogy. It describes technical details on how cluster labels are selected and how each of the three selection algorithms in comparison with labels chosen by domain experts.ReferenceCitations(Google Scholar)800 Chen, C. (2006). "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature." Journal of the AmericanSociety for Information Science and Technology 57(3): 359-377.394 Chen , C. (2004). "Searching for intellectual turning points: Progressive Knowledge Domain Visualization." Proc. Natl. Acad. Sci. USA101(Suppl.): 5303-5310.157 Chen, C., et al. (2010). "The structure and dynamics of co-citation clusters:A multiple-perspective co-citation analysis." Journal of the AmericanSociety for Information Science and Technology 61(7): 1386-1409.The most recent case study of a topic outside the realm of information science and scientometrics is a scienometric study of regenerative medicine (C. Chen, Hu, Liu, & Tseng, 2012).Chen, C., et al. (2012). "Emerging trends in regenerative medicine: A scientometric analysis in CiteSpace."Expert Opinions on Biological Therapy 12(5): 593-608.2.3Where are the Users of CiteSpace?In terms of the cities where CiteSpace were used, China, the United States, and Europe are prominent. Brazil, Turkey, and Spain also have many cities on the chart.Figure 3. Cities with users of CiteSpace between August 2013 and March 2014 are shown on the map. The colors of markers depict the level of user intensity: green (1-10), yellow (10-100), red (100-1000), and the large red water dropshaped marker (1000+).Figure 4. The use of CiteSpace in China (August 2013 – March 2014).Figure 5. The use of CiteSpace in the United States (August 2013 – March 2014).Figure 6. The use of CiteSpace in Europe (August 2013 – March 2014).3Requirements to Run CiteSpace3.1Java Runtime (JRE)CiteSpace is written in Java. It is a Java application. You should be able to run it on a computer that supports Java, including Windows or Mac.CiteSpace is currently optimized for Windows 64-bit Java 7 (i.e. Java 1.7).To run a Java application on your computer, you need to have Java Runtime (JRE) installed on your computer.3.2How do I check whether Java is on my computer?Figure 7. Select Control Panel.Figure 8. Click into the Programs category to find the Java control panel.Figure 9. Locate the Java control panel.Figure 10. Java Control Panel. Choose the Java tab and press the View button to see more detail.Figure 11. Java Runtime 1.7 is installed.3.3Do I have a 32-bit or 64-bit Computer?You need to find out whether your computer has a 32-bit or a 64-bit operating system.Go to Control Panel ►System and Security ►System. You will see various details about your computer. Under the System type, you will see whether you have a 32-bit or a 64-bit operating system.Follow the link below for further instructions on how to install Java:/en/download/help/index_installing.xmlOnce you have Java Runtime setup on your computer, you can proceed to install CiteSpace.4How to Install and Configure CiteSpaceCiteSpace is provided as a zip file for 64-bit and 32-bit computers. For Mac users, you need to download the 64-bit version.4.1Where Can I download CiteSpace from the Web?You can download the latest version of CiteSpace from the following website:/~cchen/citespace/download.htmlFigure 12.The download page of CiteSpace.After you download the zip file to your computer, unpack the zip file to a folder of your choice.Figure 13. CiteSpace is unpacked to the D drive on a computer.Now you can start CiteSpace by double clicking on the StartCiteSpace file.If you need to modify the amount memory allocated for CiteSpace (more precisely for Java Virtual Machine on which CiteSpace to be running), you can edit StartCiteSpace as a plain text file with any text editor.4.2What is the maximum number of records that I can handle with CiteSpace?This question needs to be answered at two levels: the number of records processed by CiteSpace and the number of nodes visualized, i.e. you can see and interact with them in CiteSpace.The first number is the total number of records in your downloaded dataset. CiteSpace reads through each record in your download files.The second number is determined by the selection criteria you specify and by the amount of memory, i.e. RAM, available on your computer. The more RAM you can make available for CiteSpace, the larger sized network you can visualize with a faster response rate.The speed of processing is also affected by a few computationally expensive algorithms such as Pathfinder network scaling and cluster labeling. Empirically, the best options for Pathfinder network scaling would be 50~500 nodes per slice. With faster computers or if you can wait for a bit longer, you can raise the number accordingly.The completion time of cluster labeling is related to the size of your dataset. If the entire timespan of your dataset is 100 years but you will only need to consider the most recent 10 years, it will be a good idea to carve out a much smaller dataset as long as it covers the 10 years of interest. It will reduce the processing time considerably.4.3How to configure the memory allocation for CiteSpace?The performance of CiteSpace is influenced by the amount of memory accessible to the Java Virtual Machine (JVM) on which CiteSpace is running. To analyze a large amount of records, you should consider allocating as much as memory for CiteSpace to use.You can modify the StartCiteSpace.cmd file to optimize the setting. More specifically, modify line 14 in the file. For example, -Xmx2g means that CiteSpace may get a maximum of 2GB of RAM to work with. Save the file after making any changes. And restart CiteSpace.Figure 14. Configure the memory for Java in line 14.4.4How to uninstall CiteSpaceYou can use the following steps to remove cached copies of CiteSpace from your computer.Figure 15. In a Command Prompt window, type javaws –viewer.When you see a list of cached copies of CiteSpace in the Java Cache Viewer, select the items that you want to remove and then click on the button with a red cross.Figure 16. Select a cached copy of CiteSpace and remove the item.4.5On Mac or Unix-based SystemsThe following example shows you the basic steps to get started with CiteSpace on a Mac. First, go to the CiteSpace homepage in a browser such as Chrome and download the latest 64-bit version.Figure 17. On a Mac, go to the CiteSpace home page in a browser such as Chrome and download the latest 64-bit version. Once the download is completed, follow the option “Show in Finder.” It will take you to a list of files downloaded to your Mac. The most recent file should be the zip file for CiteSpace.Figure 18. Choose “Show in Finder.”Figure 19. The downloaded zip file is shown in your Finder.Double-click on the zip file to unzip the file to a folder in the current folder.Figure 20. The zip file is unzipped to a new folder on the list.Figure 21. The new folder contains CiteSpaceII.jar and a lib folder.The simplest way to get started with CiteSpace is to open the CiteSpaceII.jar by clicking on it while holding the “Control” key on Mac. Select Open from the pop-up menu.Figure 22. Click on the CiteSpaceII.jar while holding the “Control” key and select “Open.”Due to the Java security settings, you will see a dialog box with two options for Open or Cancel.Choose Open to proceed. It will not harm your computer.Figure 23. Choose “Open” from the dialog box to proceed.After you choose Open, CiteSpace is getting started on Mac. You will see its opening page asfollows. Choose “Agree” to continue.Figure 24. CiteSpace is now started on Mac.Figure 25. Screenshots of running the Demo project of CiteSpace on Mac.It is a good idea to get familiar with the basic functions of CiteSpace by going through the Demo project on terrorism, which is included in the zip file.If you want to configure various Java Virtual Machine parameters in more detail than what is shown in the above example, you may generate a bash file for your Mac as follows.The Mac equivalent of the StartCiteSpace.cmd would be a bash file, which should have a file extension of .sh and should be executable. Let’s name the file as StartCiteSpace.sh to be consistent.1.The content of the StartCiteSpace.sh file should have the following two lines:#!/bin/bashjava -Xms1g -Xmx4g -Xss5m -jar CiteSpaceIII.jar2.The following instruction turns the StartCiteSpace.sh file to an executable file:chmod +x StartCiteSpace.sh3.To invoke the executable file, simply type its name or double click on it.StartCiteSpace5Get Started with CiteSpace5.1Try it with a demonstrative datasetWhen you installed CiteSpace for the first time, a demonstrative dataset on terrorism research is setup for you to play with and get familiar with the major analytic functions in CiteSpace.If you have never used CiteSpace before, I strongly recommend you to start with this demo dataset.To launch CiteSpace, double click on the StartCiteSpace.cmd file. You will see a command prompt window first. This window will also display various information on the status and any errors.Figure 26. The command prompt window.You will see another window of “About CiteSpace” – it displays system information of your computer, including the Java version.To proceed, you need to click on the Agree button. CiteSpace may collect user driven events for research purposes.Figure 27. The “About CiteSpace” window. To proceed, click on the Agree button.Next, you will see the main user interface of CiteSpace.The user interface is divided into left and right halves. The left-hand side contains controls of projects (i.e. input datasets) and progress report windows. The right-hand side contains several panels for configuring the process with various parameters.In a nutshell, the process in CiteSpace takes an input dataset specified in the current project, constructs network models of bibliographic entities, and visualizes the networks for interactive exploration for trends and patterns identified from the dataset.The demo project contains a dataset on publications about terrorism research. These bibliographic records were retrieved from the Web of Science. See later sections on tips for how to construct your own dataset.5.1.1The Demo ProjectWe will start the process and explain how CiteSpace is designed to help you answer some of the key questions about a knowledge domain, i.e. a field of study, a research area, or a set of publications defined by the user.Press the green GO! button to start the process.Figure 28. The main user interface of CiteSpace.CiteSpace will read the data files in the current project (Demo) and report its progress in the two windows on the left-hand side of the user interface. When the modeling process is completed, you have three options to choose: Visualize, Save As GraphML, or Cancel.Visualize:This option will take you to the visualization window for further interactive exploration. Save As GraphML:This option will save the constructed network in a file in a common graph format. No visualization.Cancel:This option will not generate any interactive visualization nor save any files. It allowsyou to reconfigure the process and re-run the process.Figure 29. CiteSpace is ready to visualize the constructed network.If you click on the Visualize button, a new window will pop up. This is the Visualization Window. Initially you will see some movements on your screen with a black background. Once the movements are settled, the background color turns to white.Let’s focus on what the initial visualization tells us and then explore what else we can find by using additional functions.First, CiteSpace visualizes a merged network based on several networks corresponding to snapshots of consecutive years. In the Demo project example, the overall time span is from 1996 through 2003. The merged network characterizes the development of the field over time, showing the most important footprints of the related research activities. Each dot represents a node in the network. In the Demo case, the nodes are cited references. CiteSpace can generate networks of other types of entities. Here let’s focus on cited references only for now. Lines that connect nodes are co-citation links; again, CiteSpace can generate networks of other types of links. The colors of these lines are designed to show when a connection was made for the first time. Note that this is influenced by the scope and the depth of the given dataset.The color encoding makes it easy for us to tell which part of the network is old and which is new. If you see that some references are shown with labels, then you will know that these references are highly cited, suggesting that they are probably landmark papers in the field. A list on the left side of the window shows all the nodes appeared in the visualization. The list can be sorted by the frequency of citations, Betweenness centrality, or by year or references as text. You can alsochoose to show or hide a node on the list.Figure 30. The Visualization window.A control panel is shown on the right-hand side of the Visualization Window. You can change how node labels are displayed by a combination of a few threshold values through sliders. You can also change the size of a node by sliding the node size slider.To answer the typical questions we asked before, let’s use several functions in CiteSpace to obtain more specific information through clustering, labeling, and exploring.5.1.2ClusteringAlthough we can probably eyeball the visualized network and identify some prominent groupings, CiteSpace provides more precise ways to identify groupings, or clusters, using theclustering function.To start the clustering function, simply click on this icon .How do I know whether the clustering process is completed? You will see #clusters on the upper right corner of the canvas. In the Demo example, a total of 37 clusters of co-cited references are identified. Each cluster corresponds to an underlying theme, a topic, or a line of research.The signature of the network is shown on the upper left corner of the display. In particular, the modularity Q and the mean silhouette scores are two important metrics that tell us about the overall structural properties of the network. For example, the modularity Q of 0.7141 is relatively high, which means that the network is reasonably divided into loosely coupled clusters. The mean silhouette score of 0.5904 suggests that the homogeneity of these clusters on averageis not very high, but not very low either.Figure 32. The clustering process is completed. 37 clusters are identified (#clusters shown in the upper right corner).Modularity and silhouette scores are shown in the signature of the network on the left.Figure 33. Members of different clusters are shown in different colors.You can inspect various measures of each cluster in a summary table of all the clusters using: Clusters ►4. Summarization of Clusters. The Silhouette column shows the homogeneity of a cluster. The higher the silhouette score, the more consistent of the cluster members are, provided the clusters in comparison have similar sizes. If the cluster size is small, then a high homogeneity does not mean much. For example, cluster #9 has 7 members and a silhouette of 1.00, this is most likely due to the possibility that all 7 references are the citation references of the same underlying author. In other words, cluster #9 may reflect the citing behavior or preferences of a single paper, thus it is less representative.The average year of publication of a cluster indicates whether it is formed by generally recent papers or old papers. This is a simple and useful indicator.Figure 34. A summary table of clusters.5.1.3Generate Cluster LabelsTo characterize the nature of an identified cluster, CiteSpace can extract noun phrases from the titles (T in the following icon), keyword lists (K), or abstracts (A) of articles that cited the particular cluster.Let’s ask CiteSpace to choose noun phrases from titles (i.e. select the T icon). This process may take a while as CiteSpace needs to compute several selection metrics. Once the process is finished, the chosen labels will be displayed. By default, labels based on one of the three selection algorithms will be shown, namely, tf*idf. Our study has found that LLR usually gives the best result in terms of the uniqueness and coverage.Figure 35. Icons for performing Clustering and Labeling functions.Cluster labels are displayed once the process is completed. The clusters are numbered in the descending order of the cluster size, starting from the largest cluster #0, the second largest #1, and so on.Figure 36. Cluster labels are generated and displayed.To make it easier to see which clusters are the largest, you can choose to change the font size of the labels from the uniformed to proportional:Display ►Label Font Size ►Cluster: Uniformed/ProportionalThis is a toggle function. That means there are two states. Your selection will switch back and forth between the two states, i.e. either using a uniformed font size or proportional.Figure 37. Set the cluster labels’ font size proportional to their size.Figure 38. Cluster labels’ font sizes are proportional to the size of a cluster. The largest cluster is #0 on biologicalterrorism.5.1.4Where are the major areas of research based on the input dataset?This is one of the primary questions that CiteSpace is designed to answer. To answer this question, we will focus on the big picture of the collection of publications represented by your dataset. Let’s make a few adjustments with the sliders in the control panel on the right so that the information of our interest will be shown clearly and information that is less relevant to this question right now will be temporarily hidden from the view.1.Node SizeAt this level, we don’t really need to see the size of a node, although it provides rich information about the history of a node. Use the slider under Article Labeling ►Node Size ►[Slide to 0] (marked by the pointer #1 in the following figure).2.Cluster Label SizeThe font size of the cluster labels are controlled by a slider with two controls: one control the threshold for showing or hiding a label based on the size of the cluster (i.e. to make sure large-enough clusters are always labeled), and the other control the font size of the cluster labels (marked by the pointer #2 in the screenshot).3.Transparency of LinksDetailed links would be useful later, but we can ignore them for now using the transparency slider to set all the links’ transparency to the lowest level, i.e. invisible. In hindsight, a more accurate term would be completely transparent.After making these minor adjustments, it will be straightforward to answer the question: Where are the major areas of research? Evidently, the largest area (cluster #0 with the largest number of member references) is biological terrorism. The second largest is posttraumatic stress (cluster #1), i.e. PTSD. The third one is ocular injury (cluster #2). The fourth one is blast (cluster #3). And there are a few smaller clusters. So now we have a general idea what constituted terrorism research during the period of 1996 and 2003. You can repeat the process on a current dataset to get an up-to-date big picture.。

CiteSpace中文手册

CiteSpace中文手册CiteSpace是一个专门用于文献可视化分析的工具，它可以帮助研究人员更加方便地进行文献调研和分析。

下面将介绍CiteSpace中文手册的相关内容，帮助用户更好地了解和使用这一工具。

首先，CiteSpace中文手册主要包括以下几个部分：简介、安装与启动、基本功能、高级功能和常见问题解答。

在简介部分，用户可以了解到CiteSpace的基本信息和功能特点，以及如何使用CiteSpace进行文献可视化分析。

在安装与启动部分，用户可以学习到如何下载和安装CiteSpace软件，并快速启动软件进行操作。

在基本功能部分，用户可以详细了解CiteSpace的基本功能，包括导入文献数据、生成知识图谱、查看节点关系等。

在高级功能部分，用户可以学习到如何使用CiteSpace进行更加深入的文献分析，包括社区发现、趋势分析等高级功能。

在常见问题解答部分，用户可以查找常见问题的解决方法，帮助用户更好地使用CiteSpace进行文献可视化分析。

除此之外，CiteSpace中文手册还提供了丰富的案例分析和操作示范，帮助用户更好地理解和掌握CiteSpace的使用方法。

用户可以通过学习手册中的案例分析，快速上手使用CiteSpace进行文献分析，提高工作效率和研究质量。

总的来说，CiteSpace中文手册是一个详细而全面的使用手册，为用户提供了丰富的功能介绍和操作指南，帮助用户更好地了解和使用CiteSpace进行文献可视化分析。

通过学习CiteSpace中文手册，用户可以快速掌握CiteSpace的使用方法，提高文献分析的效率和准确性。

愿本手册能够为广大研究人员提供便利，促进学术交流与合作。

信息计量学CiteSpace使用教程2

信息计量学CiteSpace使用教程22.CiteSpace理论知识本部分的内容主要是阐述CiteSpace被开发出来的基本设计理念。

仅追求应用的使用者可以跳过本部分，若想了解软件背后的设计理念可继续往下读。

CiteSpace的设计理念分为哲学角度和概念模型两个方面。

2.1 哲学角度•波普尔的三个世界理论。

整个世界被划分为物理世界（世界1）、精神世界（世界2）、客观知识世界（世界3）。

世界1是外在接触到的具体世界；世界2是人类脑中的精神世界，存在隐形知识；世界3是人类创造的知识体系。

传统看世界的方式是人类通过世界2来感知世界1，形成世界3。

CiteSpace是通过将世界3中的知识内容进行知识图谱可视化来认识世界1，即借助世界2通过世界3来认识世界1。

•托马斯·库恩的科学革命的结构库恩认为，科学的推进是建立在科学革命上的一个往复无穷的过程。

这个过程中会出现一个又一个的科学革命，人们的认识通过科学革命而接纳新的观点。

而新观点的重要性在于对我们所观察的对象能否作出更另人信服的解释。

库恩的科学革命是新旧科学范式的交替和兴衰。

科学认识中会出现危机，而危机所带来的新旧范式的转换都将在学术文献里留下印记。

库恩的理论给我们提供了一个具有指导意义的框架，如果科学进程真像库恩所洞察的那样，那我们就应该能从科学文献中找出范式兴衰的足迹。

•普赖斯科学前沿理论“论文会因为引证关系而形成网络，人们可以借助于图论和矩阵的方法来加以研究。

……论文一定会聚集成一团，而形成几乎绘制成地图的'陆地’和'国家’”。

基于普赖斯的论断，才形成了CiteSpace的概念模型。

•博特的结构洞理论社交网络中不是每个人和所有其他人都有直接联系，如果如此，便有了结构洞，即结构上的不完备。

这种情况下，信息在网络中的流动受到其结构上的约束。

每个人在网络中所能接触到的信息内容不再相同，传递和接受的时间也会出现差别。

Burt发现，位于结构洞周围的人往往具有更大的优势。

CiteSpace使用手册

CiteSpace使用手册CiteSpace使用手册1：安装与配置1.1 系统要求1.2 与安装1.3 配置步骤2：界面与菜单2.1 主界面2.2 导航菜单2.3 工具栏2.4 设置选项3：导入数据3.1 文件格式要求3.2 导入步骤3.3 数据预处理4：可视化分析4.1 知识图谱4.2 时间轴图4.3 关键词共现图 4.4 簇分析4.5 导出结果5：数据过滤与排序5.1 关键词过滤5.2 文献类型过滤 5.3 时间范围过滤 5.4 排序功能6：检索与搜索6.1 文献检索6.2 高级搜索6.3 检索结果导出7：图表操作7.1 缩放与平移7.2 节点与边的操作7.3 颜色与标签设置8：高级功能8.1 社会网络分析8.2 文献演化路径分析8.3 排他性分析8.4 自定义分析9：常见问题解答9.1 安装与配置问题9.2 数据导入问题9.3 可视化分析问题9.4 其他常见问题附件：本文档涉及附件，请参见附件部分。

法律名词及注释：1： CiteSpace：一款用于科学文献可视化分析的软件工具。

2：可视化分析：通过图形化的方式呈现数据，以便于观察、分析和发现数据中的模式、趋势和关联。

3：数据预处理：在数据分析之前对原始数据进行清洗、转换和归一化等处理，以达到更好的分析效果。

4：关键词共现图：展示关键词之间的共现关系，以便于分析研究领域内的热点和关联性。

5：簇分析：将文献根据某些相似性指标进行聚类，从而发现相关研究领域的研究集合。

6：社会网络分析：通过分析研究者之间的合作关系，揭示研究者、团队和机构之间的科学合作网络。

7：文献演化路径分析：分析文献之间的引用关系，揭示研究领域中的演化过程和研究方向的变化。

citespace介绍及使用

citespace介绍及使用Citespace 介绍及使用在当今信息爆炸的时代，学术研究的领域日益广泛，研究成果也层出不穷。

如何从海量的文献数据中发现知识的脉络、挖掘研究的热点和趋势，成为了科研工作者面临的一个重要挑战。

Citespace 作为一款强大的文献可视化分析工具，为我们提供了一种有效的解决方案。

Citespace 是什么呢？简单来说，它是一款由陈超美教授开发的用于分析和可视化科学文献数据的软件。

通过对文献的作者、机构、关键词、被引文献等信息进行处理和分析，Citespace 能够以直观的图形和图表形式展示知识领域的结构、演变和热点。

那么，Citespace 有哪些主要的功能和特点呢？首先，它能够绘制知识图谱。

这就像是为我们构建了一幅学术研究的地图，让我们清晰地看到不同研究主题之间的关系，以及它们在时间维度上的发展变化。

比如，通过关键词共现图谱，我们可以了解到哪些关键词在某个领域中频繁出现，从而判断出研究的热点；通过引文网络图谱，我们能够追踪重要文献的传播和影响。

其次，Citespace 具有强大的聚类分析功能。

它可以将相似的研究主题或文献自动归为一类，帮助我们快速把握研究的主要方向和分支。

这对于梳理复杂的研究领域非常有帮助，能够让我们发现那些潜在的、尚未被充分关注的研究空白。

再者，Citespace 还支持多种数据来源。

它可以处理来自 Web of Science、Scopus、CNKI 等国内外知名数据库的文献数据，为不同背景的研究者提供了便利。

接下来，让我们来了解一下如何使用 Citespace 进行文献分析。

第一步，准备数据。

我们需要从相关数据库中下载所需的文献数据，并将其保存为特定的格式，如文本格式或 Excel 格式。

第二步，安装和启动 Citespace 软件。

安装过程相对简单，按照提示进行操作即可。

第三步，设置参数。

在这一步，我们需要根据研究的目的和需求，对时间跨度、节点类型、阈值等参数进行设置。

信息计量学CiteSpace使用教程3

信息计量学CiteSpace使用教程33.主界面展示主界面本文章使用的为5.1.R8 SE版本，截至到2018年3月26日的最新版本为5.2.R2，版本选择主要依据电脑版本和所需功能确定，本文只涉及citespace的最基本功能，因此选择了在本机电脑上运行最稳定的版本。

整个界面本文认为可以分为4个主要的部分，具体如下。

1.菜单栏2.工程区3.运行进度区4.功能选择区分区3.1菜单栏菜单栏3.2工程区该区域主要用于新建工程，点击new即可以进入新工程的设置界面，具体如下：3.3运行进度区展示citespace在运行过程中的数据操作，实例演示具体如下：3.4功能选择区•Time slicing数据的切分年代•Term source 选择聚类词来源•Node type选择节点类型！！这部分的选择直接决定了生成什么样的图谱，此处将在下文做详细说明。

•Links连接强度计算Strength分析对象数据之间的连接强度Scope范围•Select criteria阈值选择标准•Pruning 剪枝方式选择（优化结果）•Visualization 可视化模式4.可以分析哪些数据？Citespace目前支持多种数据库导出的文献题录及参考文献数据，具体归纳如下：数据库及格式要求当前研究中研究英文文献主要采用web of science数据库，中文数据主要采用CNKI和CSSCI数据库。

研究者可以根据自身的需求选择数据来源，并注意其所要求的格式和文件名。

由于本文主要研究citespace的使用，因此对于数据库的数据获取不做详细说明，有需要的读者可以自行查找或关注本人更新。

需要注意的是：•所有手动下载的数据文件的文件名必须以download开头，例如download_2018.txt。

•如果需要对被引文献进行分析，必须选择具有参考文献的数据库，否则共被引部分的功能将无法实现。

citespace介绍及使用

citespace介绍及使用Citespace 介绍及使用在当今信息爆炸的时代，如何有效地处理和分析海量的数据，以获取有价值的知识和洞察，成为了各个领域研究人员面临的重要挑战。

Citespace 作为一款强大的文献分析工具，为我们提供了一种全新的视角和方法。

Citespace 是什么呢？简单来说，它是一款用于科学文献可视化分析的软件。

通过对大量文献数据的处理和分析，Citespace 能够以直观的图形和图表展示研究领域的知识结构、发展脉络以及研究热点的演变。

那么，Citespace 有哪些主要功能呢？首先，它能够帮助我们发现研究领域中的关键节点文献。

这些文献往往在学科的发展中具有重要的影响力，通过 Citespace 的分析，我们可以快速找到它们，并深入了解其核心观点和贡献。

其次，Citespace 能够揭示研究领域的热点和前沿趋势。

通过对关键词共现、突现词等的分析，我们可以清晰地看到当前研究的热点话题，以及哪些方向可能是未来的研究前沿。

此外，它还能展示研究领域的知识基础和知识结构，帮助我们理解不同研究主题之间的关系和相互影响。

接下来，让我们了解一下如何获取 Citespace 并进行安装。

我们可以在其官方网站上免费下载软件。

安装过程相对来说比较简单，按照安装向导的提示逐步操作即可。

但需要注意的是，Citespace 运行需要一定的环境配置，比如 Java 运行环境等，在安装之前要确保这些条件已经满足。

安装完成后，我们就可以开始使用 Citespace 进行文献分析了。

首先，我们需要准备数据。

Citespace 支持多种数据来源，常见的如 Web of Science、CNKI 等数据库导出的数据。

以 Web of Science 为例，我们在数据库中进行检索，选择需要的文献，然后导出为纯文本格式。

有了数据之后，我们打开 Citespace 软件，进行参数设置。

这包括时间切片的选择、节点类型的设定、阈值的调整等。

CiteSpace的使用讲解学习

citespace的使用创新知识吸收创新绩效知识转移管理知识创新知识吸收竞争优势研发视角技术网络创新知识吸收绩效知识转移管理知识战略联盟产品研发知识共享系统知识获取创新知识吸收绩效知识转移管理知识竞争优势研发视角技术网络资源观动态能力知识创造模式信息创新知识吸收绩效知识转移管理知识竞争优势研发视角技术网络战略联盟产品研发知识共享系统知识获取组织学习技术嵌入多国公司中国美国弱联系知识整合创新知识吸收绩效知识转移管理知识社区竞争优势研发视角网络战略联盟产品研发知识共享系统知识获取资源观动态能力知识创造模式信息探索利用知识溢出语义网价值创造隐性知识文化知识流机器学习创新知识吸收绩效知识转移管理知识竞争优势研发视角技术网络战略联盟产品研发知识共享系统知识获取资源观动态能力知识创造模式信息嵌入多国公司中国美国弱联系组织学习知识整合社区知识重用国际化认知创新知识吸收绩效知识转移管理知识竞争优势研发视角技术网络战略联盟产品研发知识共享系统知识获取资源观动态能力知识创造模式信息探索利用知识溢出语义网价值创造隐性知识文化知识流机器学习嵌入多国公司中国美国弱联系组织学习知识整合社区知识重用国际化认知创新知识吸收绩效知识转移管理知识竞争优势研发视角技术网络战略联盟产品研发知识共享系统知识获取资源观动态能力知识创造模式信息探索利用知识溢出语义网价值创造隐性知识文化知识流机器学习嵌入多国公司中国美国弱联系组织学习知识整合社区数据的下载sci去掉会议文献一次最多500条选择全纪录与引文选择纯文本注意将下载txt文件重命名必须以download开头例如
用途：帮助刚进入该领域研究的学者建立全面的认识；有利于分析学科的发展脉络；能够识别学科研究热点；帮助预测学科未来的发展走向。
对于研究生，可以在开题时辅助完成文献综述。
Thank you.

信息计量学CiteSpace使用教程16

信息计量学CiteSpace使用教程169. 让你的图更美——调整图谱软件自动生成的图总是很丑，相信用过citespace的人都有所体会。

虽然这样的图依然有价值，但缺乏了美感，在图谱解读时也会有部分障碍。

因此本节主要是对图谱调整的一些方法进行说明。

在图谱生成界面中的display选项中基本包含了进行图谱调整的所有内容。

图谱调整下面依次解释常用选项的用法：•调整背景颜色：Background Color/Black Background/White Background背景颜色可以根据自己的需要调整。

软件还给出了两个快捷调整的方式，直接调整为白色背景和黑色背景。

•节点调整节点调整仅能在默认图谱中进行，例如引文年环的节点，节点的形状和颜色都具有解释性含义，则无法对节点进行调整o node rendering type呈现类型o node shape节点形状o node size 节点大小o node fill color 节点填充颜色/node outline color节点轮廓颜色•标签调整o label color 选择文章标签颜色/术语标签颜色/聚类标签颜色o label font size 选择标签统一大小显示/按比例显示o label position 选择使节点标签不被遮挡/使聚类标签不被遮挡•连线o line shape 选择连接是直线还是曲线o dashed line 虚线是否显示；虚线颜色o solid line 实线是否显示；实线颜色•聚类o show/hide cluster label显示/隐藏聚类标签#o show/hide cluster ID显示/隐藏聚类IDo convex hull:shou/hide 显示/隐藏聚类区o convex hull:fill/border only 显示/隐藏聚类区阴影填充o convex hull:toggle fill color pattern填充颜色切换o convex hull:select a fill color选择填充颜色o convex hull:color by cited year聚类区按年份赋予颜色o circle show/hide显示/隐藏聚类圈\。

信息计量学CiteSpace使用教程11

信息计量学CiteSpace使用教程116.2图谱的具体含义：针对施引文献的：1.作者共现图谱根据施引文献中作者合作的情况绘制，两个作者出现在同一篇文章中即视为一次合作，主要依据作者共现频次矩阵。

2.机构共现图谱根据施引文献中机构合作的情况绘制，两个作者机构出现在同一篇文章中即视为一次合作，主要依据机构共现频次矩阵。

3.国家共现图谱根据施引文献中国家合作的情况绘制，两个作者国家出现在同一篇文章中即视为一次合作，主要依据国家共现频次矩阵。

4.特征词共现图谱从标题、摘要、作者关键词、附加关键词等来源提取特征词，根据施引文献中特征词共现的情况绘制，两个特征词出现在同一篇文献中即视为一次合作，主要依据特征词共现频次矩阵。

5.关键词共现图谱根据施引文献中关键词共现的情况绘制，两个关键词出现在同一篇文献中即视为一次合作，主要依据关键词共现频次矩阵。

6.相似度图谱计算参考文献重叠来源的相似度（新功能，较少研究论文）7.WOS学科共现图谱根据WoS数据中提供的文献所属学科，一篇文章同时属于两个WoS学科时则视为一次学科共现，主要依据学科共现频次矩阵。

针对被引文献的：1.文献共被引图谱根据被引文献同时被施引文献引用的情况绘制，两篇文献同时被一篇文献引用即视为一次共被引，主要依据文献共被引频次矩阵。

2.作者共被引图谱根据被引文献作者同时被施引文献引用的情况绘制，两位作者的两篇文献同时被一篇文献引用即视为一次共被引，主要依据作者共被引频次矩阵。

3.期刊共被引图谱根据被引文献出版期刊同时被施引文献引用的情况绘制，两本期刊的两篇文献同时被一篇文献引用即视为一次共被引，主要依据期刊共被引频次矩阵。