They briefly touched on the ability to trigger experiments. You can pretty easily do zero-suppression by simply looking at users who already regularly "like" tw

They briefly touched on the ability to trigger experiments. You can pretty easily do zero-suppression by simply looking at users who already regularly "like" tweets, and more generally by crafting a clever enough trigger you can move the distribution to be closer to normal. Basically you end up sampling a more uniform (sub)population that your experiment can at least quantify results about. If you want to focus on getting people who don't "like" tweets to start doing so, you just invert the trigger and look at that population independently. And then you have fun looking at (anti)correlations between the response of the two populations. In general it's really hard to work with non-gaussian statistics when no realistic model for the data is available, particularly when trying to apply asymptotic techniques like these. In practice it's usually easier to just try to craft a test statistic that behaves in a more friendly way, and that's where experimentalists have to be clever :)