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

Are your photos interesting?

We have dedicated a lot of effort to extracting, processing, and understanding the data from Flickr. We have also tried to analyze and use unsupervised learning methods to see if there are any patterns in the data. Luckily enough, the previous section helped us understand that there are intrinsic patterns in the data which are being used by Flickr to identify interesting photos of the day.

It would be interesting to see if we can answer the question, Will a given photo end up on the Explore page or not, by just using the metadata attributes we have been using so far in this chapter.

Preparing the data

Before we get started with building a classifier to answer the preceding question, we need some more data. Apart from the data we have collected so far (corresponding to interesting images only), we need to collect data related to photos which have never made it to the Explore page. Employing techniques similar to those we have used for collecting data for interesting...