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Sentiment Analysis in R

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

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4 Hours14 Videos52 Exercises11,579 Learners4200 XPText Mining Track

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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.
  1. 1

    Fast & Dirty: Polarity scoring

    Free

    In the first chapter, you will learn how to apply qdap's sentiment function called polarity() .

    Play Chapter Now
    Let's talk about our feelings
    50 xp
    Jump right in! Visualize polarity
    100 xp
    TM refresher (I)
    100 xp
    TM refresher (II)
    100 xp
    How many words do YOU know? Zipf's law & subjectivity lexicon
    50 xp
    What is a subjectivity lexicon?
    50 xp
    Where can you observe Zipf's law?
    100 xp
    Polarity on actual text
    100 xp
    Explore qdap's polarity & built-in lexicon
    50 xp
    Happy songs!
    100 xp
    LOL, this song is wicked good
    100 xp
    Stressed Out!
    100 xp

In the following tracks

Text Mining
Ted Kwartler Headshot

Ted Kwartler

Adjunct Professor, Harvard University

Ted Kwartler is the VP, Trusted AI at DataRobot. At DataRobot, Ted sets product strategy for explainable and ethical uses of data technology in the company's application. Ted brings unique insights and experience utilizing data, business acumen and ethics to his current and previous positions at Liberty Mutual Insurance and Amazon. In addition to having 4 DataCamp courses he teaches graduate courses at the Harvard Extension School and is the author of Text Mining in Practice with R.
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