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Mastering Social Media Mining with R

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by Sharan Kumar Ravindran & Vikram Garg
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Mastering Social Media Mining with R by Sharan Kumar Ravindran & Vikram Garg

About This Book

  • Explore the social media APIs in R to capture data and tame it
  • Employ the machine learning capabilities of R to gain optimal business value
  • A hands-on guide with real-world examples to help you take advantage of the vast opportunities that come with social media data

Who This Book Is For

If you have basic knowledge of R, in terms of its libraries, and are aware of different machine learning techniques, this book is for you. Those with experience in data analysis who are interested in mining social media data will also find this book useful.

What You Will Learn

  • Access the APIs of popular social media sites and extract data from them
  • Perform sentiment analysis and identify trending topics
  • Measure CTR performance for social media campaigns
  • Implement exploratory data analysis and correlation analysis
  • Build a logistic regression model to detect spam messages
  • Construct clusters of pictures using the K-means algorithm and identify popular personalities and destinations
  • Develop recommendation systems using collaborative filtering and the Apriori algorithm

In Detail

With the increase in the number of users on the Web, the amount of content has increased substantially, bringing with it a need to gain insights into the untapped gold mine that is social media data. For computational statistics, R has an advantage over other languages by providing readily available data extraction and transformation packages, making it easier to carry out your ETL tasks.

This book will teach you how powerful business cases are solved by applying machine learning techniques to social media data. You will learn about important 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 with R using the 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 of the implementation of various use cases using R programming.

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Ebook Details
Pages: 248
Size: 6.0 MB
Publisher: Packt Publishing
Date published:   2015
ISBN: 2370006841807 (DRM-EPUB)

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This product is listed in the following categories:

Nonfiction > Computers > Data Processing
Nonfiction > Computers > Machine Theory
Nonfiction > Computers > Mathematical & Statistical Software

These authors have products in the following categories:

Nonfiction > Computers > Data Processing
Nonfiction > Computers > Machine Theory
Nonfiction > Computers > Mathematical & Statistical Software
Nonfiction > Computers > Computer Engineering
Nonfiction > Computers > Data Visualization

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