Karma3Labs is utilizing the EigenTrust algorithm to construct a reputation and ranking system.
With the protocol, programmers may integrate on-chain reputation scoring into their communities and build suggestion and Sybil-resistance systems for web3 social network protocols. Additionally, search and discovery for consumer applications and markets can be enhanced by developers.
The founding team has built web2 infrastructure (Facebook Horizon platform, Google Cloud and PageRank) as well as web3 infrastructure (Ethereum, Harmony, Celo, libp2p). In the areas of decentralized social graphs, wallets, payments, and markets, the team collaborates with design partners.
Identity and Image on Karma3Labs
Relationships of trust and social coordination ratings
Up until now, Web3 and cryptocurrency have primarily been used in single-player modes where users transact money from their wallets (buying, selling, staking tokens or NFTs). However, blockchain is not just about financial coordination; it is also about social coordination. It must be reinforced primitives related to reputation and identity in order to promote true usefulness through social coordination.
It is relied on social networks or trust structures for web2 or analog interactions. In the early stages of file sharing, e-commerce, social media, and the sharing economy, businesses were responsible for overseeing or facilitating a consumer’s layer of trust. In the actual world, people rely on one another to verify statements or other proof of reliability. Everyday judgments that are significant require social verification of some kind.
Possibilities for the thesis to solve reputational problems
An open, transparent, and verifiable on-chain reputation system is desperately needed given the increase in users and on-chain activity. For developers, this is a big chance to construct an infrastructure of data and reputation. Web3 reputation will enable essential functionalities (search, discovery, recommendations, trust, and sybil resistance) for web3 marketplaces and consumer apps, much as site indexing and ranking became the foundation of internet search and ads.
There is still no social or peer-to-peer attestation layer, despite the Identity layer’s assistance in enabling attestations and proven credentials on the chain. Reputation is context-dependent and typically subjective. When deciding what is true or reputable about peers in a community or network, web3 users shouldn’t rely just on off-chain sources or a centralized application.
Numerous web3 applications lack reputation systems:
Which artists or creators should I trust before purchasing or minting their NFTs?
In a DAO, which community members’ opinions should one trust or consider?
Who should be chosen as a contributor for a project or community grant?
Which community members are the most devoted or long-term aligned?
Is the person behind a public key real or unique?
How It Operates: Profiling and Scoring using the EigenTrust algorithm
EigenTrust, a tool used by Karma3Labs , assists networked peers in determining the appropriate level of trust that each user should have with respect to other peers within the ecosystem. It is experimented with this first algorithm, willing to add others in the future.
Sense of intuition Karma3Labs
The foundation of trust
The fundamental tenet of EigenTrust is that an individual’s reputation is determined recursively by the reputations of those who trust them, which is then weighted by those reputations.
You can rely on your buddies as a starting point. This provides a decent foundation, but it is insufficient to create a dependable system for millions of users or peers in a network because each person can only have so many friends. You may take it a step further by finding out who your friends trust and comparing their answers to how much you trust your own friends.