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Learning Social Media Analytics with R

Learning Social Media Analytics with R

By : Sarkar, Karthik Ganapathy, Raghav Bali, Sharma
5 (4)
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Learning Social Media Analytics with R

Learning Social Media Analytics with R

5 (4)
By: Sarkar, Karthik Ganapathy, Raghav Bali, 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 (10 chapters)
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9
Index

Conventions

In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include directive."

A block of code is set as follows:

# create data frame
df <- data.frame(
  name = c("Wade", "Steve", "Slade", "Bruce"),
  age = c(28, 85, 55, 45),
  job = c("IT", "HR", "HR", "CS")
)

New terms and important words are shown in bold. Words that you see on the screen, in menus or dialog boxes for example, appear in the text like this: "selecting them from the Add filters... option box".

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.

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