balasan
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.
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.
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.