Eh, 1 is sort of why I see implicit negative feedback as more useful here. Namely, tracking the duration a user is probably giving their attention to a given item, weighted in accordance with how long you'd expect someone to give their attention to an item based on how long it is.

For example, I might see a some specific word or pattern of words in a tweet and quickly skip to the next one. That's very low friction but also a powerful signal. There are drawbacks (e.g. the long boring video that looks like something is about to happen but never does), but that's mitigated by combining this with other signals.

With 2, it's an explore/exploit trade-off. You try to explore as far and wide as you can while trying to avoid the things the user may dislike, all while sprinkling in just enough of the stuff that you know they'll like.