Source: Zhejiang Teachers Education Seminar
Software Introduction
Citespace is a literature combing software
Supports bibliographic and citation data retrieved from major sources such as Web of Science, Scopus, Dimensions, CNKI, CSSCI and some others. It can visualize the relationship between documents in front of us in the form of scientific knowledge graph .
(Image source: Citespace official website)
What can citespace do?
1. Identify research hotspots in a certain field
keyword co-occurrence
keyword burst
2. Find out the research masters in a certain field
Published (cited) author analysis
3. Find out which institutions have in-depth research in this field
Published (cited) institution analysis
The above visual map comes from the literature review in the C journal
The main functions of Citespace are very powerful
If you think citespace is helpful for you
Pay attention to the official account and reply "CS" to get the latest installation package download
Installation
1. Run jre-8u291-windows-x64.exe to make the computer have a Java runtime environment.
2. Unzip the installation package 5.7.R5W.7z
3. Open CitespaceV.jar
4. Open StartCiteSpace_Windows.bat
You can enter the following window
Enter 2 , wait for a while and the following window will pop up
Click Agree at the bottom of the window to enter the main interface
Main interface window introduction:
Upper left corner: operation area, used to build and run the project.
The first column on the right is the time slice area: you can adjust the year of the document to be analyzed, and analyze it every few years.
The second column is the text processing area: generally do not adjust, just use the original data.
The third column Node Types: the most important column, divided into four colors.
Blue area: cooperation network analysis, the objects are authors, institutions, countries;
Green area: co-occurrence analysis, objects can be topics, sources, keywords, WOS classification;
Red area: cited analysis, the objects are references, their authors, and journals;
Gray area: coupling analysis (not commonly used, interested students can do their own research)
Columns 4 and 5: Generally, it is the default setting.
The sixth column: generally select Pruning Sliced networks .
After understanding the main interface, we can enter the actual combat .
Combat articles
1. In order to facilitate the organization and storage of data , create a new folder as follows:
2. According to the subject of the research, create a subfolder , as shown in the figure below:
3. In the theme folder, create four subfolders: data\input\output\project
1. Data download
1. Taking HowNet as an example, first search for the desired topic in the advanced search .
2. Select the desired articles, for the convenience of selection, it can be set to 50 articles per page in the upper right corner display .
3. Then click Custom in Export and Analysis , click refworks and export a TXT file .
4. Rename the exported file to download_XX (HowNet can only export 500 documents at a time, if the number is greater than 500, it can be represented by file names such as download_01\download_02), and then copy the file to the input folder.
2. Data conversion
1. Return to the main interface, move the mouse to the menu window Data , and click the Input\Export button.
2. Enter the following window, click the CNKI column , click Browse after the input and output columns respectively , and select the Input\output folder we have created .
Then click the CNKI Format Conversion (2.0) button , and you can see from the figure below that the data has been converted.
3. Copy the data in the output folder to the data folder .
3. Data analysis
1. Back to the main menu, click the NEW button in the upper left corner.
2. Set the title (plain English)
PS: The title must be reset, and Untitle cannot be defaulted, otherwise the database and project library will not be able to be changed.
3. In the two columns of Project home and Data Directory, click the Browse button to open the corresponding project folder and data folder respectively . Other parameter settings remain unchanged, and click save.
4. Then go back to the right side of the main menu to adjust the parameters.
Here I set the year from 2000 to 2020.
Select the content to be analyzed in the Node Type column.
Check Pruning sliced networks in the last column .
5. After the setting is complete, click the GO button , and click Visualize in the pop-up window to visualize our data.
6. When the data tends to be stable , click the pause button (two vertical lines) in the upper left corner to get a visualized map , as follows.
4. Understanding and Adjusting Maps
Just seeing the picture above, everyone must be asking: who am I and where am I? Next, let's get a better understanding of this window and learn how to adjust the data so that the data can be displayed more clearly.
1. Know the function buttons
These two are save function buttons, the former is to save the visualization result, and the latter is to save the visualization result in PNG image format.
Start calculation and stop calculation function buttons
adjust view button
From left to right are rotate; relax; shrink; re-cluster; change line style.
Beautify View Button (Toning)
From left to right are change line color; change background color; black background; white background; auto-color by cluster; random cluster.
Adjust clustering button
They are term clustering; keyword clustering; abstract clustering; topic clustering; citation clustering; year clustering
Adjust algorithm button
The above buttons use circles to emphasize different values, such as frequency of occurrence, correlation, etc.
2. Know the data column on the left
From left to right are:
Display column: select whether the data is displayed in the graph
Frequency column: click on a number to change the sort order (largest to smallest or smallest to largest)
Relevance column: also click on the number to change the sorting order
Year of first appearance: click on the year to arrange it in chronological order (from front to back or from back to front)
keyword column
3. Know the control panel
Ⅰ Tab page (default)
Threshold: The frequency threshold of the label. The larger the value, the fewer labels are displayed, which also means that the label is more important;
Font Size: change the label font size;
Node Size: Change the size of the nodes (small circles or crosses).
Ⅱ Color and transparency page (colormap)
Skilled use can make your map clearer
Ⅲ emergent interface
Click refresh , then click view ,
A keyword emergence map can be obtained . as follows
As can be seen from the graph above, the term “mind mapping” started to gain popularity in 2016 and continued into 2020 .