Review.Network project appears like another good project that can connect to a large number of users when the platform is functional, but from my own observation, i think some how this feedback will be indirectly influenced because of the reward system, i mean, most people would like to give a good review or feedback just to be rewarded, am just trying to understand our effective this would be 100% without any influence whatsoever.
Hi D1jay! Thanks for the feedback - that is a great question. Incentivized systems can be very efficient in increasing engagement, but if you don't combine positive incentives with negative ones, than the system won't be stable. If you are only rewarding people, they will naturally try to use the system to their advantage. So what you need is a way of either making "cheating" behaviour very expensive or punishing those who don't play by the rules. The design of such a system is challenging, but also very exciting - it combines the knowledge of token models, mechanism design, blockchain technology and economy.
Here's a few words about how Review.Network's token economy works in that regard:
- Review are not validated based on sentiment. This means that a positive and negative reviews are treated the same.
- To write a review, the user must stake a certain amount of tokens, as a way to show guarantees that what he's writing is correct. If a review is approved by the process of community validation, the writer (as well as the validators) get his stake back, plus a reward. If it's rejected, the writer loses his stake and it goes back into the platform's Review Rewards Pool (a token pool from which the rewards are distributed).
- Also, to reach a decision weather or not a review should pass validation, a consensus among the validators must be formed. This means that those who are in the majority get a token reward, while those who are in minority lose their stake. The process of voting is blind, meaning that validators don't know how other validators voted until all of them have voted.
- The validators will also be "validated", by the system automatically generating reviews that it knows if they should pass the validation or not, and then punishing the validators who are clearly cheating.
- On the side of market research surveys, companies will get an automatic risk assessment for each completed one. The risk assessment is generated based on statistical models, and includes things like answering differently formulated question asking the same thing inconsistently, or detecting common non-attention patterns like straight line or zig-zag answers, as well as other well known psychometry methods.
In short - token rewards make users want to use the system, but the risk of losing their staked tokens if they cheat keeps them honest.
