Mastering Social Media Mining with R
- نوع فایل : کتاب
- زبان : انگلیسی
- نویسندگان : Sharan Kumar Ravindran, Vikram Garg
- چاپ و سال / کشور: 2015
- تعداد صفحه : 248
- شابک / ISBN : 1784396311
Description
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.
What You Will Learn
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
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.
What You Will Learn
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
