What you need for this book
by Tushar Sharma, Dipanjan Sarkar, Raghav Bali
Learning Social Media Analytics with R
- Learning Social Media Analytics with R
- Table of Contents
- Learning Social Media Analytics with R
- Credits
- About the Author
- About the Reviewer
- www.PacktPub.com
- Customer Feedback
- Preface
- 1. Getting Started with R and Social Media Analytics
- 2. Twitter – What's Happening with 140 Characters
- 3. Analyzing Social Networks and Brand Engagements with Facebook
- Accessing Facebook data
- Analyzing your personal social network
- Analyzing an English football social network
- Analyzing English Football Club's brand page engagements
- Getting the data
- Curating the data
- Visualizing post counts per page
- Visualizing post counts by post type per page
- Visualizing average likes by post type per page
- Visualizing average shares by post type per page
- Visualizing page engagement over time
- Visualizing user engagement with page over time
- Trending posts by user likes per page
- Trending posts by user shares per page
- Top influential users on popular page posts
- Summary
- 4. Foursquare – Are You Checked in Yet?
- 5. Analyzing Software Collaboration Trends I – Social Coding with GitHub
- Environment setup
- Understanding GitHub
- Accessing GitHub data
- Analyzing repository activity
- Analyzing repository trends
- Analyzing language trends
- Visualizing top trending languages
- Visualizing top trending languages over time
- Analyzing languages with the most open issues
- Analyzing languages with the most open issues over time
- Analyzing languages with the most helpful repositories
- Analyzing languages with the highest popularity score
- Analyzing language correlations
- Analyzing user trends
- Visualizing top contributing users
- Analyzing user activity metrics
- Summary
- 6. Analyzing Software Collaboration Trends II - Answering Your Questions with StackExchange
- 7. Believe What You See – Flickr Data Analysis
- 8. News – The Collective Social Media!
- Index
|
Chapter number |
Software required (with version) |
Hardware specifications |
OS required |
|
1-8 |
R 3.3.x (or higher) RStudio Desktop 1.0.x |
|
An Intel/AMD-compatible platform running Windows 2000/XP/2003/Vista/7/8/2012 Server/8.1/10 or any Unix-based OS |
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