Course
Sentiment Analysis in R
IntermediateSkill Level
Updated 05/2024Start Course for Free
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RMachine Learning4 hr14 videos52 Exercises4,200 XP13,648Statement of Accomplishment
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Course Description
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
2
Sentiment Analysis the tidytext Way
3
Visualizing Sentiment
4
Case study: Airbnb reviews
Sentiment Analysis in R
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