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Mastering Social Media Mining with R -  Ravindran Sharan Kumar Ravindran,  Garg Vikram Garg

Mastering Social Media Mining with R (eBook)

eBook Download: EPUB
2015 | 1. Auflage
248 Seiten
Packt Publishing (Verlag)
978-1-78439-967-2 (ISBN)
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Extract valuable data from your social media sites and make better business decisions using RAbout This BookExplore the social media APIs in R to capture data and tame itEmploy the machine learning capabilities of R to gain optimal business valueA hands-on guide with real-world examples to help you take advantage of the vast opportunities that come with social media dataWho This Book Is ForIf you have basic knowledge of R in terms of its libraries and are aware of different machine learning techniques, this book is for you. Those with experience in data analysis who are interested in mining social media data will find this book useful.What You Will LearnAccess APIs of popular social media sites and extract dataPerform sentiment analysis and identify trending topicsMeasure CTR performance for social media campaignsImplement exploratory data analysis and correlation analysisBuild a logistic regression model to detect spam messagesConstruct clusters of pictures using the K-means algorithm and identify popular personalities and destinationsDevelop recommendation systems using Collaborative Filtering and the Apriori algorithmIn DetailWith 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 "e;standard"e; 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.Style and approachThis easy-to-follow guide is packed with hands-on, step-by-step examples that will enable you to convert your real-world social media data into useful, practical information.
Extract valuable data from your social media sites and make better business decisions using RAbout This Book 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 dataWho This Book Is ForIf you have basic knowledge of R in terms of its libraries and are aware of different machine learning techniques, this book is for you. Those with experience in data analysis who are interested in mining social media data will find this book useful. 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 algorithmIn DetailWith 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 "e;standard"e; 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. Style and approachThis easy-to-follow guide is packed with hands-on, step-by-step examples that will enable you to convert your real-world social media data into useful, practical information.
Erscheint lt. Verlag 23.9.2015
Sprache englisch
Themenwelt Mathematik / Informatik Informatik
ISBN-10 1-78439-967-1 / 1784399671
ISBN-13 978-1-78439-967-2 / 9781784399672
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