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
About the Author
About the Reviewer
Customer Feedback

Environment setup

We will be using several R libraries or packages in this chapter as mentioned before. The major libraries which will be used along with their main utility are outlined in the following table. Feel free to use install.packages(…) to install them. For ease of usage, I have also created a file called env_setup.R which you can load into R and execute the necessary code present there to install all the necessary packages which will be used in this chapter. You can also find the package descriptions in more detail from the CRAN website at

R package

Utility description


Tools for working with APIs, URLs, and HTTP


Flexible, robust, high performance tools for working with JSON in R


A fast, consistent tool for working with DataFrame-like objects, both in memory and out of memory


A system for declaratively creating graphics, plots, and visualizations based on The Grammar...