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


We've covered a lot in this chapter so I would like to commend your efforts for staying with us till the very end! We kicked off this chapter with a detailed look into social media, its scope, variants, significance and pitfalls. We also covered the basics of social media analytics, as well as the opportunities and challenges involved, to whet your appetite for social media analytics and to get us geared up for the journey we'll be taking throughout the course of this book. A complete refresher of the R programming language was also covered in detail, especially with regard to setting up a proper analytics environment, core structures, constructs and features of R. Finally, we took a quick glance at the basic concepts of data analytics, the industry standard process for analytics, and covered the core essentials of machine learning, text analytics and natural language processing.

We will be looking at analyzing data from various popular social media platforms in future chapters so get ready to do some serious analysis on social media!