Are word clouds dead? The answer is yes, but no.

Word clouds were big 9 or 10 years ago, thanks in big part to the online application Wordle.

It only takes a quick google search of ‘word cloud’ to see how popular they were and how we absolutely used them to death. I too, am guilty of it. I’m pretty sure I created one for our annual report back in 2010 (we won’t speak of this again). Now when I see a word cloud used as a visualisation, a cold shiver goes down my spine.

A Google search of ‘word cloud’

However, there are some exceptions. I will get to this in a moment.

What is a word cloud?

In case you don’t know (or have been cast away on a desert island for the last 10 years… welcome back), word clouds are an image composed of source text that you input into a program or online application (like Wordle). It then creates an image of the text, scaling the words by how frequently they are used. You can then change the font, colour palette and layout.

They were cool, but very overused. People would dump paragraphs of text into these programs without a second thought. They can be hard to pull any meaning from and we only really pay attention to the few big words. Phrases would lose all meaning unless you grouped the words together.

I do however think there is some value left with word clouds. Hear me out…

What are they good for?

They are a good tool for qualitative analysis when you are making comparisons. Before and after, 2018 vs 2019 etc.

We used it to do a qualitative analysis of the Survive and Thrive program, which was an environmental education program delivered by the local CFA to school children in Anglesea. The paper can be found here - https://files.eric.ed.gov/fulltext/EJ1173481.pdf

We used a visual mapping exercise where children were asked a series of questions about what they would do in a bushfire and who would they give information to. This was done over two time points, before and after the CFA training.

We then used word clouds to draw comparisons between the two time points. See image below.

Example of a word cloud to make comparisons with qualitative data.

Why was it a success? Well, we can easily pull meaning from the before and after images. I have kept the same font and colour palette and we are not flooded with words.

This paper was published in 2014, and I would probably do things differently again now if I had the chance. Some of the word clouds used in the published article had words written both horizontally and vertically. The minute we change the angle of the text, the longer it takes to read and process. So I would keep all the words written horizontally.

There is one other occasion where I used a word cloud and that’s during my Design and Data Visualisation Short Course. In the PowerPoint session, I demonstrate some cool interactive tools that make your presentations more engaging. One of those is Poll Everywhere. We use it to ask questions and vote on important things (like - do you like coriander…) but I use word cloud to ask participants to use one word to describe how they are feeling about today’s course. All the answers are anonymous and they begin to appear on the screen in front of them.

Below is a screen shot from my August course. I’m just relieved no one said bored!

Word cloud used for August short course.

If I haven’t convinced you there is worth left in the old word cloud, some other ways to represent qualitative data include the following:

·      Spectrum display

·      Heat map

·      Quotes

·      Images

·      Bold text with an action colour

·      Gauge chart

·      Sunburst

·      Mind map

Ways to display qualitative information

Keep your word clouds simple with consistent font and colour palettes and only use them for comparative purposes.

And how’s this for irony, the journal that the Survive and Thrive paper is published in has the following logo…

Source: http://iajiss.org/index.php/iajiss/article/view/316/277

Back-to-back bar charts

In a recent presentation I gave on creating research impact using infographics and data visualisations, I displayed this terrible bar chart (found at https://viz.wtf/ – very funny site) as an example of what not to do.

Before. Found at https://viz.wtf/

As you can see it’s far too cluttered and busy and your eyes don’t know where to look. It’s hard to draw meaning from something this messy and your audience will probably give up before your message is properly communicated. We would be in serious trouble if this was to be printed in black and white. So, I suggested to the group that as we are comparing two groups, each with their own sub categories, we might think about turning this into a back-to-back bar chart. I left it at that.

After the presentation I thought I should put my money where my mouth is and actually create a back-to-back bar chart from this data to show how it should be done. 

This is what I came up with...

After. Designed by Alana Pirrone

Let me walk you through what I have done.

Before I begin, let me add that I created this in InDesign. I have included a tutorial below on how to create a back-to-back bar chart in Excel from Stephanie Evergreen.

Step 1

So first off, I organised the ‘hospital inpatient’ group from largest to smallest. This was no mean feat trying to match the eccentrically coloured columns with the tiny coloured legend at the bottom. You can see I have scrubbed out the Y axis on the left as we already have the values in the rows, we don’t need them twice. Bar graphs always look better and are easier to comprehend when the data are ordered. It’s less work for our brains to do. 

Cut the clutter and start to organise.

I had to use a condensed font to squeeze in the 11 categories and even used some abbreviations. I then filled the data in the first bar graph. I used one colour only and put the exact values at the end of the column so there is no ambiguity.

Step 2

Step 2 was to make the next bar graph (‘residential’) on the right, making sure I had matched up the categories correctly. It was unlikely that the data would be largest to smallest in this category, but that was only necessary in the ‘hospital inpatient’ group to guide our initial design. 

Again, I put the exact values into the rows so we wouldn’t need an axis or grid lines. You can now clearly see the patterns in the data and it’s a lot easier to follow and draw comparisons between the two groups.

Step 3

One thing in particular that I learnt in Stephanie Evergreen’s course was to display a heading that draws clear conclusions from your data. Tell your audience what you want them to see in the data. As I don’t know by whom or why this visualisation was created or what message they wanted to tell, I’m going to pretend and pull my own message from the data. 

I have colour coded the two groups ‘hospital inpatients’ and ‘residential’ to relate to their respective bar charts so there is no need to put a key in.

If I only wanted to focus your attention, just say, on the lack of beds assigned for mental health treatment in general hospitals, I can grey out all the other data and draw attention to the ‘general hospitals’ row. This is especially effective if you are using it in a presentation. All your other data is there for comparison, but you are telling your audience exactly where you want them to focus. 

So there you have it. A few easy steps to follow and we have turned something horribly busy into an easy to comprehend visualisation.

To learn how to make a back-to-back bar chart in excel, here is a tutorial from Stephanie Evergreen: https://stephanieevergreen.com/making-back-to-back-graphs-in-excel/

If you are interested to learn more about data visualisation, please take a look at my one day short course Design and Data Visualisation for Knowledge Translation. This course is designed to teach individuals ways to translate and present their work into creative and compelling visualisations. No design experience necessary.