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 will end the course by applying your sentiment analysis skills to Airbnb reviews to learn what makes for a good rental.
Sentiment Analysis in R features interactive exercises that combine high-quality video, in-browser coding, and gamification for an engaging learning experience that will make you an expert in analyzing sentiment!
What you'll learn
1. Fast & dirty: Polarity scoring
In the first chapter, you will learn how to apply qdap's sentiment function called
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 in this third chapter.
4. Case study: Airbnb reviews
Is your property a good rental? What do people look for in a good rental? Find out in chapter 4 with this Airbnb reviews case study.
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