I explain the details of how I have set this up below. It is also a good idea to correct spelling mistakes, remove plurals, remove punctuation (e.g., capitalization), and automatically combine words that are almost identical (e.g., USA, US).įortunately, there are lots of ways of doing this automatically using any number of text analysis tools. Otherwise you end up with "of", "to", "the" and "a" being the biggest words in the cloud. You typically do not want to show all words. The first step in performing a Word Cloud is to extract the words. I start by describing the overall logic, and with more detailed instructions at the end of the post.Ĭreate Your Own Word Cloud! Extracting the words Red means the tweets were used in words with a negative sentiment. Green means that the words were mainly used in tweets with a positive sentiment. The words in the Word Cloud are from tweets by President Trump. Not only do you get to see which words are most prominent, but you get an idea of the tone with which they are used. In this post, I describe how to create color-coded Word Cloud, where the colors are based on sentiment.
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