Course
Sentiment Analysis in R
IntermediateSkill Level
Updated 05/2024RMachine Learning4 hr14 videos52 Exercises4,200 XP14,052Statement of Accomplishment
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Expand Your Text Mining Skill Set
Add sentiment analysis to your text mining toolkit! Sentiment analysis is used by text miners in marketing, politics, customer service, and elsewhere. In this course you will learn to identify positive and negative language, specific emotional intent, and make compelling visualizations. You’ll start with an introduction to polarity scoring using qdap’s sentiment function, and will build your understanding of Zipf’s law and subjectivity lexicons along the way.Use Tidytext to Perform Sentiment Analysis
Sentiment, and the language used to express it, is complicated and nuanced. It’s based on linguistics, sociology, and psychology, as well as culture and slang. The second chapter in this course helps you navigate those difficulties using Plutchik’s wheel of emotion, and organizes your work using Tidytext from the Tidyverse.Bolster Your Insights with Sentiment Analysis Visualizations
Turning your sentiment analysis into clear data visualizations will help you create a clearer narrative and share your insights with the rest of the business. The third chapter of this course shows you how to visualize your sentiment analysis, and takes you beyond word clouds to create simple and impactful graphics that tell the full story of your data.You’ll finish off the course by putting all of your knowledge to the test with a case study. Using Airbnb reviews, you’ll explore what people really look for in a good rental.
Prerequisites
Text Mining with Bag-of-Words in R1
Fast & Dirty: Polarity scoring
In the first chapter, you will learn how to apply qdap's sentiment function called polarity() .
2
Sentiment Analysis the tidytext Way
In the second chapter you will explore 3 subjectivity lexicons from tidytext. Then you will do an inner join to score some text.
3
Visualizing Sentiment
Make compelling visuals with your sentiment output.
4
Case study: Airbnb reviews
Is your property a good rental? What do people look for in a good rental?
Sentiment Analysis in R
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FAQs
What is sentiment analysis?
Sentiment analysis is a form of text mining and natural language processing (NLP) performed to identify positive and negative attitudes to something, such as a product or company, within a single or multiple pieces of text. It’s important for a number of industries including marketing, politics, and customer support.
Why is R good for sentiment analysis?
R is a primarily statistical language, which makes it useful for text mining and analysis. It has a number of packages available to support sentiment analysis, as well as a large number of options to help turn that analysis into clear, high quality data visualizations.
What is tidytext?
tidytext is an R package that offers ways to convert text data into tidy formats. It helps users to switch between different tidy tools and text mining packages.
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