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
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Chapter 7. Believe What You See – Flickr Data Analysis

Through the chapters of this book, we have travelled a journey encompassing different social networks, covering varied aspects of our digital lives, and we've utilized the tools from the data science toolbox to understand them better. This penultimate chapter is about a social network which has stood the test of time and is still widely used: Flickr. Once one of the most popular kids on the block, it still stands strong with a huge user base and some interesting features. In this chapter, we will learn about this visually driven social network through the lens of a data scientist. We will leverage what we learned from previous chapters to first understand the platform followed by ways of getting data from it, and then discuss different use cases. We will also touch upon some photography basics on the way to utilize domain knowledge for better results. Let's get start; say cheese!