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

Retrieving data from Wikipedia


Wikipedia is an open source encyclopedia project developed collaboratively by multiple people across the world. This is a rich source of information, and we can find content about anything in this world. In this section, we are going to check out the ways to extract the content from Wikipedia for our analysis. We will concentrate only on the tabular content.

We will consider the Wikipedia page on List of countries and dependencies by population. This page has tabular content about the countries and their population. This is shown in the following screenshot:

Now, we will see how to bring the preceding tabular content to R so that we can perform some computation. Before going into the coding, you have to understand that the method explored is just one way of implementing it. This can be performed in multiple ways.

For the method we are discussing, we need to load the package httr and then read the URL of the mentioned Wikipedia page. We need to pass the URL to...