Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Generate a Word Cloud | Tweet Sentiment Analysis
Tweet Sentiment Analysis
course content

Course Content

Tweet Sentiment Analysis

bookGenerate a Word Cloud

A word cloud (also known as a tag cloud) is a visual representation of the most frequently used words in a piece of text. The size of each word in the cloud corresponds to its frequency of use, with the most frequently used words appearing larger and more prominent than less frequently used words.

Word clouds are often used to quickly and easily identify the most important or relevant words in a piece of text, such as a document, a webpage, or a set of social media posts. They can be used in a variety of applications, such as text mining, content analysis, and social media monitoring.

Task
test

Swipe to show code editor

  1. Import WordCloud, STOPWORDS, ImageColorGenerator from wordcloud.
  2. Select only the "neutral" tweets (the "sentiment" column).
  3. Create a plot using the plot_wordcloud() function.

Mark tasks as Completed
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

A word cloud (also known as a tag cloud) is a visual representation of the most frequently used words in a piece of text. The size of each word in the cloud corresponds to its frequency of use, with the most frequently used words appearing larger and more prominent than less frequently used words.

Word clouds are often used to quickly and easily identify the most important or relevant words in a piece of text, such as a document, a webpage, or a set of social media posts. They can be used in a variety of applications, such as text mining, content analysis, and social media monitoring.

Task
test

Swipe to show code editor

  1. Import WordCloud, STOPWORDS, ImageColorGenerator from wordcloud.
  2. Select only the "neutral" tweets (the "sentiment" column).
  3. Create a plot using the plot_wordcloud() function.

Mark tasks as Completed
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 1. Chapter 9
AVAILABLE TO ULTIMATE ONLY
We're sorry to hear that something went wrong. What happened?
some-alt