Visualizing Data: Text Clouds

  1 m, 15 s

Mullets. If you have one, they're awesome, and they're certainly visually gripping.  

In recent weeks, we've been getting a lot of requests for "creating Tag Clouds with Salience." This has caused a lot of consternation and angst amongst us, because we feel that we're failing our customers. 

First and foremost, if you don't know what a word cloud is, go here:  http://www.wordle.net/

Now, try to forget that you've even seen them. Here's a blog post that's going to tell you, in gory detail, just why they are so bad:  http://www.niemanlab.org/2011/10/word-clouds-considered-harmful/

To summarize this article, and to put this in our own words, it comes down to this: you can't measure anything from them. You can't compare them. They are form without much in the way of function – the packing algorithms simply try to get all the words into the space, and if you remove one word, the cloud will look completely different.  

Here's a wonderful example of someone who really likes word clouds, and from Stanford nonetheless:  https://dhs.stanford.edu/algorithmic-literacy/using-word-clouds-for-topic-modeling-results/

Our experience is that text clouds are the visualization that people ask for when they don’t really have an idea of what they are trying to show and don't understand the questions they're going to have to ask.

Sort out your question first, and then understand how you want to visualize, don't just jump to a word cloud because they're pretty and look "texty."  

Categories: Insights, Text Analytics, Text Clouds