Book Image

Learning Social Media Analytics with R

By : Dipanjan Sarkar, Karthik Ganapathy, Raghav Bali, Tushar Sharma
Book Image

Learning Social Media Analytics with R

By: Dipanjan Sarkar, Karthik Ganapathy, Raghav Bali, Tushar Sharma

Overview of this book

The Internet has truly become humongous, especially with the rise of various forms of social media in the last decade, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the reader to understand the current social media landscape and to learn how analytics can be leveraged to derive insights from it. This data can be analyzed to gain valuable insights into the behavior and engagement of users, organizations, businesses, and brands. It will help readers frame business problems and solve them using social data. The book will also cover several practical real-world use cases on social media using R and its advanced packages to utilize data science methodologies such as sentiment analysis, topic modeling, text summarization, recommendation systems, social network analysis, classification, and clustering. This will enable readers to learn different hands-on approaches to obtain data from diverse social media sources such as Twitter and Facebook. It will also show readers how to establish detailed workflows to process, visualize, and analyze data to transform social data into actionable insights.
Table of Contents (16 chapters)
Learning Social Media Analytics with R
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Accessing GitHub data


There are various ways to access data from GitHub just like we have seen in the previous chapters for other social media platforms. If you are using R, you can go ahead and use the rgithub package which provides a high level interface with several functions to retrieve data from GitHub. Besides that, you can also register an application with GitHub to get an OAuth-based access token which can be used to gain access to GitHub's own API. We will cover both mechanisms briefly in this section.

Using the rgithub package for data access

As we mentioned earlier, there is a specific package in R known as rgithub which provides high level functions and interfaces to access GitHub data. You can install and load the package in R using the following code snippet:

library(devtools)
install_github("cscheid/rgithub")
library(github)

Of course, you would then need a GitHub application ID and secret token to gain seamless access to the data without too many restrictions and rate limits...