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Sentiment Analysis in R

via Datacamp


Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

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.


Fast & dirty: Polarity scoring
-In the first chapter, you will learn how to apply qdap's sentiment function called polarity() .

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.

Visualizing sentiment
-Make compelling visuals with your sentiment output.

Case study: Airbnb reviews
-Is your property a good rental? What do people look for in a good rental?

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