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 your personal social network


As we had mentioned before, Facebook is a massive social graph, connecting billions of users, brands and organizations. Consider your own Facebook account if you have one. You will have several friends who are your immediate connections, they in turn will have their own set of friends, and you might be friends with some of them and so on. You and your friends form the nodes of the network and edges determine the connections. In this section, we will analyze a small network of you and your immediate friends and also look at how we can extract and analyze some properties from the network. Before we jump into our analysis, we'll start by loading the necessary packages needed, which are mentioned in the following snippet, and store the Facebook Graph API access token in a variable:

library(Rfacebook)
library(gridExtra)
library(dplyr)
# get the Graph API access token
token =  'XXXXXXXXXXX'

You can refer to the file fb_personal_network_analysis.R for code snippets...