Hacker News Reader

Comment by ric2b | Hacker News Reader

This has been tried in the cryptocurrency space, people start faking accounts to upvote their content and make money.

So basically what already happens with reddit/twitter/etc but amplified because you give them a direct financial incentive to upvote low effort crap.

View on HN

That doesn't really work when they have to pay for each account they use to upvote though.

Even if they boost their own post a bit for it to get the attention of others, they're still paying $2 per upvote for that. And if their post is no good, people might even just cancel those out with downvotes.

It is essentially a perfect recipe for money laundering.

This would be the most inefficient way to launder money ever. You'd get at most 50% of the money you took in (realistically, more like 30-40% with taxes if you were transferring significant volume), and you'd have to have an active account that posted a lot of legitimate-sounding comments, and at least 10K sockpuppet accounts which you'd then need to script a way to upvote all the posts by the account you're intending to launder it through.

That's assuming the site lets 10K+ users sign up and pay with crypto, or you have the time to track down and signup for 10K prepaid burner cards. Then, after allo that, you'd have to hope that the site never detects the vote manipulation, since you'd have an account that's getting tons of upvotes from a specific set of users.

Really.. I think this is the worst idea for laundering money I've ever heard of. You'd be better off walking into a casino and putting it all on blackjack until you win a big hand, then reporting the winnings.

Agreed. It's way more efficient to sell $10,000 cabinets named "Julia" on Wayfair.

I think it can be solved by personalizing the top page(s), so you mostly see the kind of stuff you upvote. If there are a few people up-voting crap you wont see it, but they will see all of it.

I'm building https://linklonk.com which works this way - you get content ranked based on what you upvoted. This is to make the incentives for voting aligned and help prevent abuse.

I think the problem with karma/reputation systems is that the source of karma are fungible - anyone's upvote has the same effect on the reputation. And this makes it gameable.

A personalized system can solve this by replacing global reputation with user-to-user trust. Now it matters who upvoted - a random bot or a user whose past contributions have been useful to you.

>Now it matters who upvoted - a random bot or a user whose past contributions have been useful to you. //

In that system how do you create a ranked list of content for a user to browse? Isn't it going to be very heavy on processing demand?

You can do the processing in a worker. Maybe even offload it to the client. If there is a live stream a pretrained machine learning model could be used and it could infear who will like what

Yes, it requires keeping track of how much each user trusts each other user. And then when you rank content for user A, you use the trust table of user A as weights of upvotes.

This is more computationally intensive than sorting by the raw number of upvotes or weight upvotes by karma/popularity.

But I think this is a useful computation - the user can be more confident that the content they is is not astroturfed and comes from trustworthy users.

Details of how trust is calculated: https://linklonk.com/item/3292763817660940288

Reply on news.ycombinator.com