How to Handle Scopus Data in CiteSpace

Here is a new demo video of creating visualizations with #Scopus data in #CiteSpace.
https://youtu.be/Pr5CeiIq8A0

CiteSpace 5.4.R4 has revised the way to process data downloaded from Scopus in the RIS format.
One interesting change is the option of using article titles instead of the journal titles for cited references. As a result, in a network of co-cited references we will be able to see the article titles directly, which should be more informative than see the corresponding journal titles only. The length of the title is limited to 50 letters. Titles longer than that will have a trailing ... to indicate they have been chopped off. If you prefer the previous style, which is consistent with the Web of Science format, you can select that option accordingly at the time of coversion.
The References section of Scopus data is still highly volatile to put it politely. References without author information at all will be discarded not becaues they are not important, rather because it is a warning sign of something very unpredictable.
Some references of articles originally appeared in Chinese contain references in English and then in Chinese. When possible, the English version will be retained. If references are in Chinese entirely, then they will be processed.
The figure below shows a network of cited references derived from 1,126 records from a search on Scopus (title, keyword, abstract). Some discrepencies are obvious - you may use the alias trick to unify them.

The figure below shows a list of publications with citation bursts. Note their article titles are shown instead of their journal titles.

Here are some step-by-step screenshots so that you can check with your own settings:
Step 1: Convert RIS files exported from Scopus:


Step 2: Remove duplicates from the converted data folder. This is in fact to speed up the later process.


Step 3: Create a new project for the converted Scopus data:



Step 4: Fine tune visualizations, including labeling clusters with title words from the citers of a cluster or from the members of a cluster.

Step 4a: Burst detection for citation bursts that last for at least 5 years:

Step 4b: Label clusters with title words from citing articles to corresponding clusters:

Step 4c: Label clusters with title words from cited references of each cluster (Currently, this function is only available for Scopus data).

Step 4d: Timeline view visualization: