The voting is based on a pagerank reputation system. Users earn reputation from getting thier comments upvoted and, in turn, increase the rank of the posts they upvote. This makes rankings sybil-resistant making manipulation harder and moderation easier. So far its been a great way to keep communities focused and resistant to mob mentality.
Each community manages their own reputation system (admins are in the personalization vector).
There is also a prediction-market mechanism overlayed on top of the rankings — you can bet on post's relevance within a given community (this is abstracted from the UX at the moment).
Interesting. Could you explain the prediction market/betting system in more detail? Can users wager Coins, upvotes, or repuptation that they get back multiplied by some factor that depends on the success of the post they bet on, or do I misunderstand?
> an attack wherein a reputation system is subverted by forging identities in peer-to-peer networks [...] named after the subject of the [1973] book Sybil, a case study of a woman diagnosed with dissociative identity disorder. The name was suggested in or before 2002 by Brian Zill at Microsoft Research
Users can wager Relevant Coins (not reputation) on the quality of posts. This is done via a 'bonding curve market maker' (https://blog.relevant.community/how-to-make-bonding-curves-f...). The market maker mints 'shares' in exchange for staking Relevant Coins. The more shares are outstanding the more expensive they are, thereby rewarding early participants.
Not that the actual ranking of the post is determined via the pagerank algorithm which is independent of the coins and betting.
If the post has a higher ranking than average it gets a portion of the newly minted tokens — kind of like block rewards. These rewards get distributed to all the users that staked on the post proportional to the amount of shares they own. Everyone also gets their original tokens back. So in reality this it's prediction market 'light'. All users pay a 'tax' on their token balance via the inflation rate and but get a chance to win a portion of the pot by participating in curation.
The betting mechanism is similar to and inspired by Steemit. Except they don't use reputation ranking to resolve the market. Steemit posts are ranked by how many tokens were staked on them, so a whale can basically force the market and get all the rewards — self-fulfilling prophecy. In our case its is more akin to an actual prediction market where the prediction is separate from outcome. At scale the prediction market can actually be a useful way to surface recommendations.
We are experience trust scarcity in online media because trust hasn't been part of social media's business model. By extension it stopped being part of the news publication's business model (everyone is forced to compete for clicks). That and because on the internet, nobody knows you're a dog.
Ironically we are increasingly willing to get into stranger's cars and allow strangers stay at our homes because a few corporations like Uber and Airbnb were able to quantify, materialize and monetize trust. So it's not that much of a stretch to imagine an internet where trust plays a role in the way we distribute, consume and exchange information online. Hacker News is a case in point.
Ready for the shill?
We're building Relevant to make it easy to set up communities similar to HN, each with its own trust/reputation metric (based on personalized pagerank algorithm). So instead of using clicks / votes, all users and content get a trust/reputation score. The result is that rankings don't represent popularity, but relevance, resulting in better feeds and making communities easier to moderate. These trust metrics are much more resistant to sybil/sock-puppet attacks and can be used to build healthier business models, from prediction markets to advertising.
I think the issue is too much trust. Too many people believe that because a Network, Publication, Author, or Anchor published quality work in the past, therefore, they can be trusted to reliably deliver news in the future. People's sources, access, knowledge, agenda, and effort vary wildly and each story needs to be judged on its own merit.
Right, so maybe scarcity of trustworthiness, or trust metrics/signals is more accurate. Plenty of popularity/click metrics, but how often do we really want to know what the masses think about complex nuanced topics?
The voting is based on a pagerank reputation system. Users earn reputation from getting thier comments upvoted and, in turn, increase the rank of the posts they upvote. This makes rankings sybil-resistant making manipulation harder and moderation easier. So far its been a great way to keep communities focused and resistant to mob mentality.
Each community manages their own reputation system (admins are in the personalization vector).
There is also a prediction-market mechanism overlayed on top of the rankings — you can bet on post's relevance within a given community (this is abstracted from the UX at the moment).
Disclosure, I'm the founder.