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.
In the first chapter, you will learn how to apply qdap's sentiment function called polarity() .
In the second chapter you will explore 3 subjectivity lexicons from tidytext. Then you will do an inner join to score some text.
Make compelling visuals with your sentiment output.
Is your property a good rental? What do people look for in a good rental?
In the following tracksText Mining
DatasetsLine by line polarity for 4 books4 books as a tidy data frame4 books as DocumentTermMatricesPolarity scores of Boston Airbnb reviewsHousing rental reviews from Airbnb in Boston
PrerequisitesText Mining with Bag-of-Words in R
Adjunct Professor, Harvard University
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