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

Revisiting analytics workflow

As discussed in detail in Chapter 1, Getting Started with R and Social Media Analytics (see A typical social media analytics workflow), we defined some key steps involved in the analysis of data from different social networks. Continuing with the same theme for Twitter, the different use cases we will work on in the next sections can also be broken down into the following key steps:

  • Data access

  • Data processing and normalization

  • Data analysis

  • Insights

The data access step involves understanding the APIs and their corresponding R packages to tap into the social network. We've already talked about creating a Twitter app and did a quick connect and extraction of tweets using R. Each of the following sections will make use of the same initial step for data access and then build upon them based on the requirements. We will discuss and provide details for each of the other steps in this workflow as we progress with the use cases. Stay tuned.