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

Challenges to news data analysis

The analysis of news data was probably one of the most challenging tasks in this book. We will try to give the reader a summary of the toughest problems that we encountered in the process of developing this chapter:

  • Lack of API sources: News data providers are not always very API friendly. We were lucky to have a prestigious source such as The Guardian, which believes in open access to its data and goes to great lengths to ensure that. But, apart from a couple of big names such as The New York Times and The Guardian, we won't find a lot of data providers going down the API route.

  • Web scraping: Web scraping HTML data for text is quite a complex process. Once again, we were lucky that the HTML structure for our data sources was quite simple. A more involved structure would have meant a larger and more elaborate process of data scraping. (We encourage the reader to take a look at the HTML structure for any New York Times article to realize the complexity that...