Social Media Analytics with R
4.4 (40 ratings)
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Social Media Analytics with R

Acquire Social Media from Twitter, Google+ and Facebook, transform, analyzer and produce insights
4.4 (40 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
389 students enrolled
Created by V2 Maestros, LLC
Last updated 1/2017
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Current price: $10 Original price: $100 Discount: 90% off
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  • 3.5 hours on-demand video
  • 2 Articles
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Appreciate how businesses use Social Media data
  • Learn how to extract Social Media data
  • Transform Social Media data to be ready for analytics
  • Execute a number of use cases for Social Media analytics
View Curriculum
  • R Programming and RStudio familiarity

Everyone is using social media to share their life experiences, initiate ideas and provide opinions  in a free and open way. Businesses are hence interested in understanding what people think and say about their products and services. They are augmenting their business applications to extract, understand and analyze social media data about them. If you are working or hoping to work in the analytics world, you need to enrich your skill set with social media analytics to improve your market value.

This Social Media Analytics with R course helps you achieve exactly that ! It introduces you to the tools and technologies required to extract social media data. Twitter, Facebook and Google interfaces are covered. It then walks through multiple use cases for analyzing this data and generating business insights. The examples range from simple histograms to advanced machine learning techniques. After completing this course, you will be able to execute end-to-end social media analytics projects and integrate them with existing business applications.

This course requires previous R experience.

Who is the target audience?
  • Analytics Professionals
  • IT Students
  • Data Analysts
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Curriculum For This Course
28 Lectures
3 Lectures 06:55

Resource Bundle for the Course
Social Media Analytics Overview
5 Lectures 38:55

Data present in Social media - content, links and comments

Preview 03:58

Social Media Applications

What challenges exist that are specific to social media analytics

Challenges with Social Media Applications Development

An Overview of REST API technologies

REST API Overview

An introduction to authentication and authorization with OAuth

OAuth Overview

Social Media Analytics Quiz
3 questions
Twitter Analytics
2 Lectures 22:00

An overview of twitter data, authentication and authorization

Twitter data API overview

Examples of using TwitterR libraries for connecting to twitter and extracting data

Getting Twitter data with R
Google+ Analytics
2 Lectures 12:56

How to setup Google+ APIs for data extraction

Google+ data API overview

Examples of using Google R library to connect to Google+ and extract data

Getting Google+ data with R
Facebook Analytics
2 Lectures 17:27

An overview of Facebook data, authentication and authorization

Facebook data API Overview

Examples of using Facebook R library to connect to Facebook and extract data

Getting Facebook data with R
Analytics Use Cases
7 Lectures 49:46

Introduction to the types of use cases covered in this course

Preview 02:30

Perform basic frequency analysis

Frequency Analysis

Perform sentiment analysis of tweets and posts

Sentiment Analysis

Analyze links - friends, followers and and find patterns

Link Analysis

Understand social media actions and find patterns

Action Analysis

Extract deep meanings - find items that frequently occur together and understand what they mean

Frequent Pattern Mining

Get real time streaming data from social media and then analyze them in real time and extract meaning

Real time Data Analysis
Advanced Topics
5 Lectures 50:42

Types of machine learning - Supervised and unsupervised.

Machine Learning Overview

Converting text into numeric representation using TF-IDF


Use clustering to group similar messages with R

Clustering messages with R

Classify messages into pre-defined classes using Naive Bayes Classification algorithm

Classifying messages with R

Linking social media data with enterprise data sources

Linking data from other sources
2 Lectures 01:18

BONUS Lecture : Other courses you should check out
About the Instructor
V2 Maestros, LLC
4.1 Average rating
3,035 Reviews
30,591 Students
13 Courses
Big Data Science / Analytics Experts | 25K+ students

V2 Maestros is dedicated to teaching big data / data science at affordable costs to the world. Our instructors have real world experience practicing big data and data science and delivering business results. Big Data Science is a hot and happening field in the IT industry. Unfortunately, the resources available for learning this skill are hard to find and expensive. We hope to ease this problem by providing quality education at affordable rates, there by building data science talent across the world.