We tend to think that "misleading"or "deceptive" charts are ones that employ
visual tricks, such as inverted or truncated axes.
The effects of such visual tricks have been widely studied. But how
common are they in practice? And do they actually work for spreading misinformation?
In other words: is this how people actually lie with charts?
We analyzed 10,000 COVID data visualizations shared on Twitter and we find that visual tricks
are not as widespread as one might think. Instead, we describe much more common
and nuanced techniques, such as assigning causality and cherry-picking, among others.