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


I really appreciate and commend your efforts to stay with me to the end of this chapter. We went on a long and fruitful journey looking at the possibilities of tapping the potential goldmine that exists in Facebook's data stores. We looked at the Graph API and the Rfacebook package and harnessed it efficiently to extract and curate data from Facebook. We covered several important use-cases to understanding the basic use of the Graph API, analyzing your own personal social network of friends, and even learnt concepts of social network analysis by leveraging the igraph package. We built on these concepts and analyzed an even larger social network of Facebook brand pages related to English Football and applied more advanced concepts of social network analysis. Finally, we looked at Facebook page data and analyzed brand page and user engagements on Facebook, based on several different attributes and variables. We also mined trending posts and influential users from this data. You now...