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


Flickr is one of the longest-standing social networks and it has evolved over the years. Pretty much like Flickr, we have progressed through this book and evolved our methods and techniques across chapters. Flickr presented its own set of challenges and the following is a quick summary of these:

  • API response objects: Flickr has a nicely documented and updated set of APIs which provide access to most of its publicly usable content. The challenge comes from the design and response of these APIs. While the design of the APIs is something for which Flickr engineers must have put in a lot of thought, they pose difficulties for analytical use cases. It is difficult to use multiple API methods to extract data related to a single entity and so on. On the same lines, the response objects are deeply nested and require some thought and creativity before one can preprocess and use the data for any analysis. Moreover, any changes to the APIs may require extensive rework with regards to extraction...