zlacker

An idea I mull over occasionally: what if you could spend your karma points to boost any given post? This would ultimately be another form of paid advertising, except that the currency used would be earned by contributing to the community. Then, allow people to sell their karma points for fiat currency. Companies would buy karma points directly from users in order to promote their self-promotional posts, but those posts would be subject to the same rules and moderation as any other post. That way you're actually paying your best users rather than charging them.

>>kokane+(OP)
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.

>>ric2b+6F
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.

>>ric2b+6F
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.

>>z3t4+MN
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.

>>pcthro+001
It is essentially a perfect recipe for money laundering.

>>janals+i91
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.

>>lonk11+851
>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?

>>pcthro+1i1
Agreed. It's way more efficient to sell $10,000 cabinets named "Julia" on Wayfair.

>>kokane+(OP)
tweakers.net (a Dutch tech site that's been around since the 1998) allows you to spend your karma points in their Karmastore on things like custom-css, RSS-feeds in tracker and custom newsletter.

>>pbhjpb+aE1
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

>>pbhjpb+aE1
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