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Introduction to Text Analysis in R

Intermediate

4.5+

Updated 12/2024

Analyze text data in R using the tidy framework.

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RData Manipulation4 hours15 videos46 exercises3,850 XP23,849Statement of Accomplishment

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Course Description

From social media to product reviews, text is an increasingly important type of data across applications, including marketing analytics. In many instances, text is replacing other forms of unstructured data due to how inexpensive and current it is. However, to take advantage of everything that text has to offer, you need to know how to think about, clean, summarize, and model text. In this course, you will use the latest tidy tools to quickly and easily get started with text. You will learn how to wrangle and visualize text, perform sentiment analysis, and run and interpret topic models.

Prerequisites

Introduction to the Tidyverse

1

Wrangling Text

Text as data

Airline tweets data

Grouped summaries

Counting categorical data

Counting user types

Summarizing user types

Tokenizing and cleaning

Tokenizing and counting

Cleaning and counting

2

Visualizing Text

Plotting word counts

Visualizing complaints

Visualizing non-complaints

Improving word count plots

Adding custom stop words

Visualizing word counts using factors

Faceting word count plots

Counting by product and reordering

Visualizing word counts with facets

Plotting word clouds

Creating a word cloud

Adding a splash of color

3

Sentiment Analysis

Sentiment dictionaries

Counting the NRC sentiments

Visualizing the NRC sentiments

Appending dictionaries

Counting sentiment

Visualizing sentiment

Improving sentiment analysis

Practicing reshaping data

Practicing with grouped summaries

Visualizing sentiment by complaint type

4

Topic Modeling

Latent Dirichlet allocation

Topics as word probabilities

Summarizing topics

Visualizing topics

Document term matrices

Creating a DTM

Evaluating a DTM as a matrix

Running topic models

Fitting an LDA

Tidying LDA output

Comparing LDA output

Interpreting topics

Naming three topics

Naming four topics

Introduction to Text Analysis in R

Course
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*4.5

from 22 reviews

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Most recent
Top reviews

Sebastian N.

2 months

Excellent introduction

Edwin A.

9 months

I found this course a great introductory course to learn analyzing text data using R.

Eric M.

9 months

I loved it!

Feri P.

11 months

good

sabine b.

12 months

In a couple of hours, I learnt enough to write a piece of code to understand reviews from consumer ratings (and other cases). I definitely want to learn more.

"Excellent introduction"

Sebastian N.

"I found this course a great introductory course to learn analyzing text data using R."

Edwin A.

"I loved it!"

Eric M.

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