I've thought about that a fair amount also. I think the key is personalization. If bad actors downvoted a bunch of items, it would only affect people who alread

I've thought about that a fair amount also. I think the key is personalization. If bad actors downvoted a bunch of items, it would only affect people who already shared a lot of similar votes with those actors. That is still exploitable: if I know you like A, B, and C, (perhaps those are popular items), I could also upvote those items and then downvote another item D. I have an idea for countering this: keep track of history. So instead of just measuring ratings overlap ("of items you've both rated, 75% of items were rated the same"), you keep track of the performance of recommendations made from that user ("of Alice's items that we recommended to Bob, Bob upvoted them 25% of the time"). I haven't thought about this super deeply yet, but I think to beat that, you'd have to actually provide valuable data to the system in the first place.