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 trend analysis

You may wonder why we are doing a sentiment-based analysis again, and the reason is a simple one: it is obvious analysis to do when the data is a large corpus of text. In our case, it is even more important as news and sentiment are closely related. If you can deduce the sentiment-based theme of a large corpus of news data, then it means that you have gained an important insight into what might be a long and tedious process of classifying each document manually. Simple at it may seem, it is one of the most coveted tools of any text data miner.

For our use case, we will do an interesting analysis. We will go through The Guardian's articles with a mention of Indian Prime Minister Narendra Modi and try to see how the sentiment trends about him have changed over the years.

Getting the data – not again

In the last section, we came to understand the building blocks of data gathering from normal web pages. We will build a strategy around that procedure to extract the necessary...