Mastering Social Media Mining with R

More Information
  • Access APIs of popular social media sites and extract data
  • 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

With an increase in the number of users on the web, the content generated has increased substantially, bringing in the need to gain insights into the untapped gold mine that is social media data. For computational statistics, R has an advantage over other languages in providing readily-available data extraction and transformation packages, making it easier to carry out your ETL tasks. Along with this, its data visualization packages help users get a better understanding of the underlying data distributions while its range of "standard" statistical packages simplify analysis of the data.

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

With this handy guide, you will be ready to embark on your journey as an independent social media analyst.

  • 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
Page Count 248
Course Length 7 hours 26 minutes
ISBN 9781784396312
Date Of Publication 22 Sep 2015


Sharan Kumar Ravindran

Sharan Kumar Ravindran is a data scientist with over 5 years of experience and is currently working with a leading e-commerce company in India. His primary interest lies in statistics and machine learning, and he has worked with multiple customers across Europe and the U.S. in the e-commerce and IoT domains. He holds an MBA degree with specialization in marketing and business analysis. He conducts workshops, partnering with Anna University, to train their staff, research scholars, and volunteers in analytics. In addition to co-authoring Data Science Essentials with R by Packt Publishing, Sharan has also co-authored Mastering Social Media Mining with R by Packt Publishing. He maintains, a website with links to his social profiles and data blog.

Vikram Garg

Vikram Garg (@vikram_garg) is Senior Analytical Engineer at a big data organization. He is passionate about applying machine learning approaches in any given domain and creating technology to deepen human intelligence. Vikram graduated in computer science and electrical engineering from IIT Delhi. In his free time, he enjoys playing tennis and swimming.