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We tend to think that "misleading"or 
"deceptive" charts are ones that employ

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visual tricks, such as inverted or truncated axes.

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The effects of such visual tricks 
have been widely studied. But how

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common are they in practice? And do they 
actually work for spreading misinformation?

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In other words: is this how 
people actually lie with charts?

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We analyzed 10,000 COVID data visualizations 
shared on Twitter and we find that visual tricks

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are not as widespread as one might think.
Instead, we describe much more common

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and nuanced techniques, such as assigning 
causality and cherry-picking, among others.