Book Image

Mastering Social Media Mining with R

Book Image

Mastering Social Media Mining with R

Overview of this book

With an increase in the number of users on the web, the content generated has increased substantially, bringing in the need to gain insights into the untapped gold mine that is social media data. For computational statistics, R has an advantage over other languages in providing readily-available data extraction and transformation packages, making it easier to carry out your ETL tasks. Along with this, its data visualization packages help users get a better understanding of the underlying data distributions while its range of "standard" statistical packages simplify analysis of the data. This book will teach you how powerful business cases are solved by applying machine learning techniques on social media data. You will learn about important and recent developments in the field of social media, along with a few advanced topics such as Open Authorization (OAuth). Through practical examples, you will access data from R using APIs of various social media sites such as Twitter, Facebook, Instagram, GitHub, Foursquare, LinkedIn, Blogger, and other networks. We will provide you with detailed explanations on the implementation of various use cases using R programming. With this handy guide, you will be ready to embark on your journey as an independent social media analyst.
Table of Contents (13 chapters)
Mastering Social Media Mining with R
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Rfacebook package installation and authentication


The Rfacebook package is authored and maintained by Pablo Barbera and Michael Piccirilli. It provides an interface to the Facebook API. It needs Version 2.12.0 or later of R and it is dependent on a few other packages, such as httr, rjson, and httpuv. Before starting, make sure those packages are installed. It is preferred to have Version 0.6 of the httr package installed.

Installation

We will now install the Rfacebook packages. We can download and install the latest package from GitHub using the following code and load the package using the library function. On the other hand, we can also install the Rfacebook package from the CRAN network. One prerequisite for installing the package using the function install_github is to have the package devtools loaded into the R environment. The code is as follows:

install.packages("devtools")
library(devtools)
install_github("Rfacebook", "pablobarbera", subdir="Rfacebook")
library(Rfacebook)

After installing...