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 English Football Club's brand page engagements


Continuing our analysis of Facebook pages, let us now focus our analysis on brand page engagements. Each page on Facebook belonging to a commercial entity is basically a prestigious brand and keeping proper engagement with its followers on Facebook is very important. In this section, we will pick up three prestigious top tier football clubs from the Premier League and analyze their brand page engagements, trending posts and influential users using various analyzes and visualizations by retrieving data from their Facebook pages. We will also be using a multiplot(…) function for depicting multiple ggplot2 plots together. The code is present in the multiple_plots.R code file which you can load along with the other dependencies as shown here:

library(Rfacebook)
library(ggplot2)
library(scales)
library(dplyr)
library(magrittr)
source('multiple_plots.R')

The code used for analysis in this section is available under the file named fb_page_data_analysis...