Sentiment Analysis in R

中级技能水平

更新时间 2024年5月

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

课程描述

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.

先决条件

Text Mining with Bag-of-Words in R

Fast & Dirty: Polarity scoring

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

课程描述

Expand Your Text Mining Skill Set

Use Tidytext to Perform Sentiment Analysis

Bolster Your Insights with Sentiment Analysis Visualizations

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