Reputation building on OpenSquare Network
In last post, we introduced collaboration mining in OpenSquare Network. Reputation building is another key feature of OpenSquare.
Build reputation from users' collaboration data
OpenSquare first is a platform to facilitate users' collaborations. There maybe many collaboration ways and we can track users' behavior in the collaboration process. For example:
- A hunter don't submit the task on time
- Funder or hunter get a good remark from each other
- A funder pay the task fee in a very late time
Blockchain keep the collaboration data open and can not be changed, and this make it possible for us to track them and build the reputation in a trustable way.
We define behaviors in OpenSquare. Each behavior will have a corresponding reputation score. When users' behavior data grows, the reputations are built from these behaviors data. There will be 3 kinds of reputation scores.
It's a simple sum up of users' behaivor scores, and it has no range limitation. So the value is in (-∞, +∞).
We normalize the behavior score to value range (0, 100) to help user to judge the reputation score. It will be useful for example when a funder want to compare reputation between hunters.
Human being may have many personality characters, and each may be involved with different kinds of behaviors. So user can sum up the scores of a group of behaviors, and we call it feature scores.
How reputation can be used
We build reputation from collaboration, and then the reputation will help collaboration in return. The reputation will be used in following ways.
- Task funders can choose target hunters by their reputation score
- Task hunters will follow funders with higher reputation score
- Users' with higher reputation will be recommaned more by OpenSquare to collaboration partners
- Polkadot ecosysem para-chains can query users' reputation score and do customized services