CheckerChain Whitepaper

CheckerChain: Next-Gen AI-powered Crypto Review Platform

ABSTRACT. Existing online review platforms are not able to solve the problem of manipulated and fake reviews. Traditional centralized review platforms do not even incentivize users for their contributions. We believe these problems are due to the lack of a consensus mechanism in review architecture. Utilizing blockchain technology will partially solve the need of transparent and tamper-proof reviews.

In this paper, we propose an AI-powered trustless review consensus mechanism (tRCM) on top of MultiversX protocol. This tRCM architecture enables reviewers to meet a consensus on an opinion without the need of knowing each other's opinions and completely removes the chance of fake or manipulated reviews to receive any incentives.

PREFACE

This protocol is experimental; can suffer from parameter changes and logical upgrades. Improved methodologies can be integrated upon rigorous revisions from both the core team and the community. This paper outlines the most up-to-date version of this protocol which is intended to be completely open-source to develop the desired review aggregator platform.

2. INTRODUCTION

There are hundreds of thousands of crypto projects, products, companies, books, movies, and events happening every day. It is a real hassle to find the best product when we have to trust the feedback and reviews from unknown or known parties without any consensus mechanism. The existing review system is completely broken and unfair as there is no trustless check system to avoid paid, promoted, or faked reviews.

Company name

Per year revenue

Monthly user

Market Share

TripAdvisor

604m USD

160m

TrustPilot

102m USD

57.3m

1.5%

ProductHunt

3.3m USD

6.23m

Better Business Bureau

215m USD

13.83m

Yelp

872.9m USD

142.5m

Google

282b USD

88.33b

73%

Facebook

85.96b USD

18.13b

We introduce a decentralized and trustless review protocol built on MultiversX where opinion-checkings are incentivized on meeting a consensus. Millions of these users can get revenue shared with CheckerChain. Posters, Reviewers, and Influencers are rewarded based on the quality of their work with $CHECKR token.

CheckerChain is a next-gen AI-powered crypto review platform built on MultiversX using trustless review consensus mechanism (tRCM). Anyone can become a Poster to publicly list any crypto products and anyone can nominate themselves in tRCM protocol to participate in reviewing process. Reviewers are arbitrarily selected from the nominee pool by the protocol in zero-knowledge conditions. While the tRCM protocol is utilized for reviewing only crypto related products in CheckerChain platform, there exists a "tRCM-as-a-Service (tAAS)" extension to implement tRCM across multiple categories such as movies, books, electronics, cities, restaurants, hotels, and more.

3. INTERACTION ON CHECKERCHAIN

CheckerChain uses tRCM protocol, an evolutionary upgrade of the existing review industry with a decentralized philosophy. Hence, our protocol is built on MultiversX, which is the most decentralized, the most secure and the most valueable blockchain network.

CheckerChain operates with 3 user types:

(a) Posters: users who list crypto products on CheckerChain (b) Reviewers: users who are nominated by tRCM protocol to write reviews (c) Influencers: users who interact, boost, and engage on CheckerChain

4. tRCM ARCHITECTURE

tRCM is an acronym for trustless Review Consensus Mechanism. It is the core protocol utilized on CheckerChain to make reviews trustless.

tRCM is based on 2 assumptions for a review to hold any authentic value,

reviews are performed in zero-knowledge proofs without any control of either the poster or the reviewer.
honest reviewers in the protocol always establish a majority

In tRCM protocol, anyone can participate but the protocol selects the reviewers arbitrarily to review a product. Selected reviewers can only get reward for their work when their review score falls in consensus range. Closer the consensus, more the reward.

Reviewers have a higher probability to make their review closer to consensus only when they are honest. Any dishonest review by any reviewer falls outside of consensus. This generates no or least reward making dishonest reviews highly expensive to perform. This will eventually discourage such attackers from participating in the tRCM protocol.

These scores are vital parameters to derive incentives for each contribution.

Trust Score: This is an atomic data of a product calculated from reviewer's task. It represents rating of a product in the range of 0 to 100.
Normalized Trust Score: This is a derived data of a product calculated from Trust score to determine the impact on reward. Posters receive reward based on Normalized Trust score.
Consensus Score: This is an atomic data of reviewer's task. It represents the quality of trust score in the range of 0 to 100.
Profile Score: This is both an atomic and aggregated data of reviewer's performance. It represents the quality of consensus in the range of 0 to 100. Reviewers receive reward based on Profile score.
Rating Score: This is a derived data of a product calculated as Trust score out of 5 and processed with Bayesian Average.
Feedback Score: This is an aggregated data of reviewer's task combined with influencer's task. It represents sentiments of a product in the range of 0 to 5.
Normalized Feedback Score: This is a derived data calculated from Feedback Score; processed with Bayesian Average.
Sentiment Score: This is a categorical data of a product from reviewer's task. It is non-numerical in category and numerical inside a category in the range of 0 to 100.
Ranking Score: This is a derived data of a product calculated from Rating score and Consensus score. It represents the rank of a product starting from 1 over 24h, 7 days, 30 days and All-Time ranges.

4.1 Trustless Review Process

When a product gets listed on CheckerChain, tRCM protocol enacts on 30 parameters of 10 categories to generate 3 vital atomic scores: Trust Score of Product, Profile Score of Reviewer and Consensus Score of Review Cycle.

10 Categorical Metrics of CheckerChain for Crypto Reviews

Project (Innovation/Technology)

Userbase/Adoption

Price/Revenue/Tokenomics

Utility Value

Security

Social Presence

Partnership (collab, VCs, exchanges)

Team

Roadmap

Clarity & confidence

5. PROTOCOL INCENTIVES

CheckerChain protocol incentivizes all contributions made by anyone within the ecosystem. When the majority of participants are honest, the trustless review consensus mechanism (tRCM) becomes secure and realistic. This protocol is designed to distribute incentives based on the consensus level of tRCM achieved.

Initially, for 8 years, incentives are maintained by distributing the new tokens. When 250,000,000 $CHECKR tokens get completely distributed at the end of 8 years, the inflation rate drops to 0%, and incentives are maintained by distributing revenues earned by the platform.

Protocol incentives are distributed on a monthly basis and counted as Epoch. The contributions of posters, reviewers and influencers are collectively accounted per epoch into performance scores. Based on these monthly scores, rewards are emitted by the Distributor Smart Contract. All scores get reset every epoch.

Any contributions on CheckerChain platform are incentivized through its own MultiversX digital assets called $CHECKR.

6. UTILITIES & ECOSYSTEM

CheckerChain is a utility-driven decentralized application (dApp). It fixes the problem of fake and manipulated review systems and is also designed with a gamified review-to-earn ecosystem.

6.1 Trustless Review Platform

CheckerChain is a next-gen AI-powered trustless review platform. This is one of the most innovative evolutions in the review industry. While CheckerChain is particularly focused on the crypto and blockchain segment, it is a much-needed upgrade that can be experimented with in all other categories where reviews are important.

6.2 Review-to-Earn Platform

Traditional review platforms have no mechanism to incentivize contributors without impacting review metrics. CheckerChain integrates tRCM bringing fairness to review metrics while also incentivizing all contributors.

6.3 tRCM as a Service (TaaS) for third-parties

tRCM is a revolutionary protocol. It does not need to be limited within a platform. Hence, tRCM as a Service (TaaS) model is available for any third parties to utilize tRCM. It can extend from a crypto review platform to multiple segments such as movies, books, electronics, cities, restaurants, hotels, and more.

6.4 Revenue Sharing

Posters, reviewers, and influencers are automatically rewarded. As the platform grows to generate revenues, participants in this ecosystem can act as beneficiaries.

6.5 Asset Utility (Payment for Services, Staking, Liquidity-Providing)

$CHECKR tokens can be utilized as payment for various services where tRCM is implemented. Holders can earn rewards for staking or providing liquidity.

6.6 Gamified UX

CheckerChain is an interactive web3 platform where contributions are incentivized and boosted through a gamified model. UI and UX are designed to support various achievements, badges, digital artifacts, and leaderboards.

7. TOKENOMICS

$CHECKR token is a MultiversX native digital asset. The maximum supply of $CHECKR token is 2,100,000,000 and it has 5 decimals.

Distribution

Amount ($CHECKR)

Allocation %

Early Investors

58,000,000

2.76%

Reviewers Incentives

150,000,000

7.14%

Posters Incentives

50,000,000

2.38%

Influencers Incentives

50,000,000

2.38%

Staking Incentives

75,000,000

3.57%

LP Incentives

175,000,000

8.33%

Market Making DEX/CEX

146,000,000

6.95%

Bridges to DEX/CEX

150,000,000

7.14%

Business Development

250,000,000

11.90%

Market Development

346,000,000

16.48%

Investors/VCs

200,000,000

9.52%

Team Development

100,000,000

4.76%

Advisors Incentives

100,000,000

4.76%

Foundation Reserve

250,000,000

11.90%

TOTAL

2,100,000,000

100%

7.1 Distribution scheduled within 8 years are Reviewers Incentives, Posters Incentives, Influencers Incentives, Advisors Incentives, Team Development, LP Incentives, and Staking Incentives. The distribution curve of 8 years is maintained at 18%, 17%, 16%, 14%, 12%, 10%, 8%, and 5% in chronological order.

Time Period

8-year Distribution

Example: Poster Incentives

1st year period

18%

9,000,000

2nd year period

17%

8,500,000

3rd year period

16%

8,000,000

4th year period

14%

7,000,000

5th year period

12%

6,000,000

6th year period

10%

5,000,000

7th year period

4,000,000

8th year period

2,500,000

7.2 Revenue allocations:

Allocations

8-year Distribution

After 8-year

Posters

10%

Reviewer

30%

Influencers

10%

Stakers

10%

Liquidity Providers

10%

Leaderboard

00%

10%

Foundation

100%

20%

7.3 Reward Distribution:

Method

Calculation Basis

Period

Distribution

Poster

Trust Score

1st of Month