Learning Social Media Analytics with R

Tap into the realm of social media and unleash the power of analytics for data-driven insights using R
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Learning Social Media Analytics with R

Raghav Bali, Dipanjan Sarkar, Tushar Sharma

Tap into the realm of social media and unleash the power of analytics for data-driven insights using R
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Book Details

ISBN 139781787127524
Paperback394 pages

Book Description

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

Chapter 1: Getting Started with R and Social Media Analytics
Understanding social media
Social media analytics
Getting started with R
Data types
Data analytics
Machine learning
Text analytics
Summary
Chapter 2: Twitter – What's Happening with 140 Characters
Understanding Twitter
Revisiting analytics workflow
Trend analysis
Sentiment analysis
Follower graph analysis
Summary
Chapter 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
Summary
Chapter 4: Foursquare – Are You Checked in Yet?
Foursquare – the app and data
Category trend analysis
Recommendation engine – let's open a restaurant
The sentimental rankings
Venue graph – where do people go next?
Challenges for Foursquare data analysis
Summary
Chapter 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
Summary
Chapter 6: Analyzing Software Collaboration Trends II - Answering Your Questions with StackExchange
Understanding StackExchange
Data Science and StackExchange
Demographics and data science
Challenges
Summary
Chapter 7: Believe What You See – Flickr Data Analysis
A Flickr-ing world
Accessing Flickr's data
Understanding Flickr data
Understanding interestingness – similarities
Are your photos interesting?
Challenges
Summary
Chapter 8: News – The Collective Social Media!
News data – news is everywhere
Sentiment trend analysis
Topic modeling
Summarizing news articles
Challenges to news data analysis
Summary

What You Will Learn

  • Learn how to tap into data from diverse social media platforms using the R ecosystem
  • Use social media data to formulate and solve real-world problems
  • Analyze user social networks and communities using concepts from graph theory and network analysis
  • Learn to detect opinion and sentiment, extract themes, topics, and trends from unstructured noisy text data from diverse social media channels
  • Understand the art of representing actionable insights with effective visualizations
  • Analyze data from major social media channels such as Twitter, Facebook, Flickr, Foursquare, Github, StackExchange, and so on
  • Learn to leverage popular R packages such as ggplot2, topicmodels, caret, e1071, tm, wordcloud, twittR, Rfacebook, dplyr, reshape2, and many more

Authors

Table of Contents

Chapter 1: Getting Started with R and Social Media Analytics
Understanding social media
Social media analytics
Getting started with R
Data types
Data analytics
Machine learning
Text analytics
Summary
Chapter 2: Twitter – What's Happening with 140 Characters
Understanding Twitter
Revisiting analytics workflow
Trend analysis
Sentiment analysis
Follower graph analysis
Summary
Chapter 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
Summary
Chapter 4: Foursquare – Are You Checked in Yet?
Foursquare – the app and data
Category trend analysis
Recommendation engine – let's open a restaurant
The sentimental rankings
Venue graph – where do people go next?
Challenges for Foursquare data analysis
Summary
Chapter 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
Summary
Chapter 6: Analyzing Software Collaboration Trends II - Answering Your Questions with StackExchange
Understanding StackExchange
Data Science and StackExchange
Demographics and data science
Challenges
Summary
Chapter 7: Believe What You See – Flickr Data Analysis
A Flickr-ing world
Accessing Flickr's data
Understanding Flickr data
Understanding interestingness – similarities
Are your photos interesting?
Challenges
Summary
Chapter 8: News – The Collective Social Media!
News data – news is everywhere
Sentiment trend analysis
Topic modeling
Summarizing news articles
Challenges to news data analysis
Summary

Book Details

ISBN 139781787127524
Paperback394 pages
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