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

Analyzing repository trends


In this section, we will focus on various ways to analyzing different aspects of repositories, which include visualizing repository creation and updates over time, looking at various repository metrics and the various relationships among them. To start with, you can load up the necessary dependencies and the trending_repos.RData dataset which we created in the previous section in case you haven't done so already:

source('load_packages.R')
load('trending_repos.RData')

Now we are ready to analyze various trends with regard to our trending repositories and each of the following sub-sections will focus on a particular aspect of repository trends.

Analyzing trending repositories created over time

We will look at the trends with regard to our trending repositories based on their creation date over time. Basically we want to view the repository creation frequency over time and observe if there are any peaks or dips from the graph which we will be plotting. Our dataset has...