Let's build a word cloud!

Sentiment Analysis in Python

Violeta Misheva

Data Scientist

Word cloud example

an example of a word cloud with black background

How do word clouds work?

The more frequent a word is, the BIGGER and bolder it will appear on the word cloud.

Word cloud generated by one of the longest reviews

a circle-shaped word cloud from a review about the Titanic

Why word clouds?

Pros

Can reveal the essential
Provide an overall sense of the text
Easy to grasp and engaging

Cons

Sometimes confusing and uninformative
With larger text, require more work

Let's build a word cloud in Python!

from wordcloud import WordCloud
import matplotlib.pyplot as plt

two_cities = "It was the best of times, it was the worst of times, 
        it was the age of wisdom, it was the age of foolishness, 
        it was the epoch of belief, it was the epoch of incredulity, 
        it was the season of Light, it was the season of Darkness, 
        it was the spring of hope, it was the winter of despair, 
        we had everything before us, we had nothing before us, 
        we were all going direct to Heaven, we were all going
        direct the other way – in short, the period was so far
        like the present period, that some of its noisiest
        authorities insisted on its being received, for good
        or for evil, in the superlative degree of comparison only."

Define the WordCloud object

cloud_two_cities = WordCloud().generate(two_cities)

# To see all arguments of the function
?WordCloud

Background color
Size and font of the words, scaling
Stopwords

# How does cloud_two_cities look like?
cloud_two_cities
<wordcloud.wordcloud.WordCloud at 0x2585f286d68>

Displaying the word cloud!

plt.imshow(cloud_two_cities, interpolation='bilinear')

plt.axis('off')
plt.show()

a wordcloud with black background, built from the first sentence of Tales of two cities

Let's practice!

Sentiment Analysis in Python