If you have read this book, please leave a review on Amazon.com. Potential readers can then use your unbiased opinion to help them make purchase decisions. Thank you. The $5 campaign runs from December 15th 2020 to January 13th 2021.
This is the code repository for Learning Social Media Analytics with R, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.
The Internet has truly grown humongous especially in the last decade with the rise of various forms of social media, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the user to understand the current social media landscape and how analytics can be leveraged to derive insights from it. This data can be analyzed for gaining valuable insights into the behavior and engagement of users, organizations, businesses, and brands. It will help readers in framing business problems and solving those 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, Facebook, and so on. It will also guide readers in establishing detailed workflows for processing, visualization, and analysis of data to transform social data into actionable insights.
All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter 03.
The code will look like the following:
install.packages("Rfacebook")# install from CRAN
# install from GitHub
library(devtools)
install_github("pablobarbera/Rfacebook/Rfacebook")
| Chapter number | Software required (With version) | Hardware specifications | OS required |
|---|---|---|---|
| 1-8 | R 3.3.x (or higher) | At least 1 GB of RAM, a mouse, and enough disk space for recovered files, image files, etc. | An Intel\AMD compatible platform running Windows 2000, XP/2003/Vista/7/8/2012 Server/8.1/10 or any unix based OS |
| RStudio Desktop 1.0.x | A network connection for installing packages, connecting to social networks and downloading datasets |
For Chapter01, use the code given in the chapter
If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.