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

Recommendation engine – let's open a restaurant

An important reason for including a recommendation engine as one of our use cases is to emphasize how we can link the existing data to frame it as an analytics problem and then to use existing solutions to solve it reliably. We don't expect to have cutting edge accuracy with this recommendation engine but we use it to give you a healthy learning of working on such problems as and when they arrive. Before we dive into building a recommendation engine, a (very) brief introduction is appropriate.

Recommendation engine – the clichés

Recommendation engines (or systems) are one of the most recognized machine learning applications in the industry today. To say that a lot of people equate recommendation engines to machine learning won't be an exaggeration. They command such immense visibility for a simple reason: they integrate with business and they work. A recommendation engine is ubiquitous in today's technology landscape. They are present on e-commerce...