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

Sentiment analysis

Twitter timelines are the new battlegrounds for brands, fans and organizations to fight it out and present a winner. Twitter is also a place where users usually rant about their disappointments or share their happiness. The dynamics of human interaction and our urge to share opinionated views on wide ranging topics, from cat pictures to wars and everything in between, have reached an altogether different level.

With its 300 million plus users and counting, Twitter is a virtual country in itself! Its huge user base which generates tweets (or opinions) by the count of millions every minute present a unique opportunity to study and utilize human sentiment and/or opinions. This study of our sentiments and emotion carries a lot more value than just pure academic research (which is, of course, still required by any standards). It carries a lot of business value for companies, governments and celebrities alike.

Before we dive into implementation details and a particular use case...