What is R?
R is a data analysis tool: data scientists, statisticians, analysts, and others who need to make sense of data use R for statistical analysis, data visualization, and predictive modeling.
R is an open-source software project. It’s totally FREE. The source code of R is also open for inspection and modification to anyone who wants to see how the methods and algorithms work under the covers.
There are thousands of websites that offer tutorials to learn R. It’s best to start of simple like “Try R code school”, which is a step by step guide for learning the basics of R. There are a total of 8 Chapter Badges that can be “earned”. Once you completed the tutorial, you will be awarded a badges, like below:
Example using R?
As a researcher, Google Scholar Citations lets you track citations to your publications over time. Recently, I found an interesting R package, called Scholar.
This scholar package provides functionality to extract citation data from Google Scholar. It allows you to compare multiple scholars and predict future h-index values. There’s a full guide on Github (along with the source code).
Now I will show you step by step how to use this package to extract information.
1. Download and Install Scholar package
You can download this package from CRAN.
Once the download finished, you can install the package by typing in the R Console:
2. Get profile data from a Google Scholar
Once you opened a Google Scholar profile page, the URL will contain a string that ends with user=qj74uXkAAAAJ. To use this Scholar package, you need to reference scholars by this id. For example Stephen W. Hawking’s data:
3. Compare multiple scholars
You can also compare multiple scholars, for example Stephen W. Hawking and Albert Einstein:
4. Predicting future h-index values
A scholar’s h-index is n if they have pulished at least n papers that have been cited at least n times each. Now we show how to use the scholar package to predict future h-index values:
Result is :