CheckerChain — what are we building?

Sonika Baniya
3 min readJun 29, 2022

A decentralized review aggregation platform

CheckerChain protocol is a review-to-earn ecosystem that powers up a decentralized review aggregator platform to check products for their validity and authentic feedback. All the information regarding the app (along with use cases, whitepaper, light paper) is here https://docs.checkerchain.com/

The main idea of CheckerChain is to bring trustless reviews that are written and validated by the checkers (users of CheckerChain).

How is CheckerChain a trustless review aggregation platform?

  • Each post is reviewed by an anonymous group of reviewers who review a post on basis of pre-defined binary questions.
  • Each question has a different weightage value of the answer so the weightage of each question can be different.
  • The individual score is calculated according to the response.
  • A collective final score is calculated for one post from anonymous reviewers.

In this whole process above, there is no way a review can be manipulated because reviewers are anonymous.

The review process and scoring of review in Checkerchain

Why should we trust the review of anonymous reviewers?

The CheckerChain system maintains the performance score of each reviewer. That means with every response logged by the reviewer, the system checks if the review is democratically accepted by other reviewers or not (by checking whether the response falls on the majority response or not). So, there is a high chance the reviewer won't respond falsely or carelessly. More importantly, this performance score is a key parameter of incentive reviewers will be getting. So, as a user, we can trust the review from reviewers.

How is the scoring done in CheckerChain?

Checker Scoring

Each number of responses and average of responses is weighted under the Bayesian average. Bayesian average use two constants to offset the arithmetic average of an individual product. One is the arithmetic average (m), second is a confidence number(C).

Coding the Bayesian Average to Checker Score :

Let's take some examples of no of responses and their average checker score

Checker Score calculation
  • Each post receives a certain no of responses from the reviewer
  • Each individual score is simple arithmetically averaged into an average score
  • Every Confidence number is calculated on the base of the no of responses for each product, where C is equal to the 25% percentile.
  • Based on the above average and confidence number, every average checker score is breakdown into a weighted average.

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