A little while ago I noticed some really interesting graphs composed entirely of emoji and I’ve been keen to gather a bunch of examples together. I like “EmojiVIz” because it’s engaging, succinct and if done well, really informative and memorable. Case in point: some of the EmojiViz included this post I remember seeing ages ago, and a bit of googling helped me find them again 🤓.
The examples I’ve found all come from Twitter. The tweet format requires extra creativity due the the 240-character limit coupled with the width-constraint of the tweet.
A note on accessibility, and this is quite an important one – I think emoji visualizations in their current form must play havoc on screen-readers. While I don’t think the use of emojiViz will become very widespread, it would be great if Twitter could recognise it as an image and perhaps convert it to one and allow for alt-text. I think that would help a lot.
Onward to the cool visualizations!
Here’s two examples of New Zealand and French weather on a map. If you’re familiar with the countries it really easy to understand them.
Here’s an alternative map of the French weather with the legend displaying a “comfort level” based on the temperature.
Here’s an example of an air quality map, also from France. The legend is displayed below the map, and the pinned tweet holds more legend detail.
The French accounts show a lot of creativity. At the end of this post I’ll link to a meme inspired by the weather maps.
This @Biological account is the best at creating EmojiViz. I’ll refrain from re-posting the account’s entire timeline. Here’s just one showing the relative CO2 emissions of different food types. It highlights the difficulty of being able to keep the whole chart in one nice square when there’s outliers in the data and your smallest unit has to be 1. It still has a good effect though.
Here’s one showing number of wins.
This is the oldest one I’ve seen, dating all the way back to 2011! A text-based bar chart using Unicode block elements.
These are automated tweets showing the progress against a timeline. Here we have the progress through the current year, and another showing progress against the US President’s current term in office.
The year progress bar uses Unicode block elements, whereas the President progress bar is pure text. One displays the data label to the right outer end of the bar, whereas the other contains the value in what is effectively the chart title.
A simple timeline showing key events throughout a typical day.
Not really sure what to call this one. Is distribution correct?
A really effect visualization showing the demographic composition of a population.
Simple ranking of items, pure text. Legend is built into the viz showing change in position.
Ranking international data with flags is a popular use of EmojiViz. At first it may be a bit difficult if you don’t recognize the flags, but its a great way to learn what they are.
The next two rankings are text-based and describe the same data. This shows the league points the soccer clubs of Liverpool and others had accrued when Liverpool won the English Premier League. The first graph is very effective at showing the gap between first and second place. The second ranking graph fills the space in-between the two gaps with humour.
This next ranking isn’t too easy on the eye, but it packs a load of information in a small space. It’s ranking the use of emoji in a 48hour period.
This example is using the effect of highlighting numbers that you want to have stand out, along with descriptive icons.
This example is a replacement for what you might call a Big Number. In this case, it shows the leverage created from public spending.
I’m really not sure what to call these :).
This is not a visualization per-se, I suppose more of an Infographic of sorts with icons attached to the label.
This one is a mix of progress and a picture. It’s shows the progression of spring with each cherry blossom depicting 10% progress. Adding the GIF is a nice touch.
This one is a short biography of prominent scientists. What I like about this is that because you have to work a little bit to decipher it, the info is a bit more memorable! This had the added effect of making Mullis stand out by being so different to the others. So I googled Mullis and found out he was a biochemist who worked on synthesizing psychedelics :).
Here’s an explanation of some scientific concepts. Again, not a data visualization exactly, but it is using simple data to explain something.
And some more Data + Science:
This one gets an Honourable Mention 🙂
Ok, back to the French weather account. This is really fun combo of data visualization, trolling with funny memes and possibly some social and political commentary thrown in for good measure.
First, our beloved TweeteoFrance account posted this EmojiViz of the weather:
Then the spawned a series of “corrections” by users! If you’re familiar with Twitter, you can follow the individual threads, quotes and replies to see them all, but I’ve picked out a few. I don’t know what all of them mean but they’re funny anyway!
That’s a wrap. If you’ve found other good examples, please share them with me via Twitter or reply to any newsletters I send out 🙂 .