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Mastering Social Media Mining with R

You're reading from  Mastering Social Media Mining with R

Product type Book
Published in Sep 2015
Publisher
ISBN-13 9781784396312
Pages 248 pages
Edition 1st Edition
Languages
Concepts

Table of Contents (13) Chapters

Mastering Social Media Mining with R
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Fundamentals of Mining 2. Mining Opinions, Exploring Trends, and More with Twitter 3. Find Friends on Facebook 4. Finding Popular Photos on Instagram 5. Let's Build Software with GitHub 6. More Social Media Websites Index

Business cases

Some of the business cases that can be implemented using the GitHub data are as follows:

  • Identify the popular programmers in different languages.

  • The online courses' websites can target potential subscribers based on suitable patterns in behavior.

  • Provide recommendations to users on which user to follow as well as which repository to look out for.

  • Identify the best people to target for a new open source project development in Java.

  • Plot the trend on languages; here, the data point will be the number of repositories in a language. In order to get the trend, we need to pull the data on a daily basis to know how many new repositories are created and which language is used to develop them. This will help in understanding the lifecycle of language popularity.

  • Build a regression model to predict the number of watchers a repository would get within a month of launch.

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