Book Image

Mastering Social Media Mining with R

Book Image

Mastering Social Media Mining with R

Overview of this book

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.
Table of Contents (13 chapters)
Mastering Social Media Mining with R
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Social media mining


In simple terms, social media mining is a systematic analysis of information generated from social media. It becomes necessary to tap into this enormous social media data with the help of today's technology, which is not without its challenges. Data stream is a prime example of Big Data. Dealing with data sets measured in petabytes is challenging, and things like signal-to-noise ratio need to be taken into consideration. It is estimated that around 20 percent of such social media data streams contain relevant information.

The set of tools and techniques, which are used to mine such information, are collectively called Data mining technique and in the context of social media it's called social media mining (SMM). SMM can generate insights about how much someone is influencing others on the Web. SMM can help businesses identify the pain points of its customer in real time. In turn, this can be used for proactive planning. Identification of potential customers is a very important problem every business has been trying to solve for ages. SMMs can help us identify the potential customers based on their online activities and based on their friend's online activities. There has been a lot of research in multiple disciplines of social media:

  • Why does social media mining matter?

  • If you can measure it, you can improve it

  • Modeling behavior

  • Predictive analysis

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