Review

Reviews convey credibility opinions succinctly.

Rate and comment

Ethos reviews follow a negative, neutral and positive rating standard. Because it's so universal, it's easy to embed in any context without confusing anyone. It's second nature. It also provides both quantitative and qualitative feedback.

Sybil Who?

Ethos requires that you have a valid Ethos profile (and thus invitation to Ethos) before one can leave reviews. This has the benefit of reducing spam and sybil attacks.

Reviews are not anonymous; they include who left the review.

Impact on Credibility

Reviews influence the credibility score. The extent to which they adjust the score depends on the credibility consensus. A few of the ways reviews have impact include:

  • High credibility reviewers will have more impact, per-review

  • Reviews may be normalized per reviewer; someone who only leaves positive reviews may have less impact. Same for someone only leaves negative reviews

  • The age and volume of reviews

  • Reviewers vouching you, or vouched by you, have more impact

This will be thoroughly documented and transparent through our Credibility Score.

Philosophy

Reviews are fast and free. Thus they are a weaker but earlier signal. They may be a fluke or provide an early warning sign.

Reviews provide a lightweight way to provide feedback, even publicly denounce someone, before progressing to actions with financial stakes such as vouching, unvouching or slashing.

One should be able to earn a reputation before one has substantial funds or a large network. Reviews facilitate that.

Under the hood

The review interface is intentionally simple and adaptable. Apps can add tags, keys, or text for capabilities customized for specific markets or audiences. Stay tuned for additional details on how you can integrate reviews into your own product.

Future opportunity

Opinions and true feelings are often lost to fear of social repercussions. Ethos reviews today are onchain and require a profile, so everyone can see exactly how people perceive each other.

If the highest social signals we can get are from anonymous opinions, how can we leverage the Ethos credibility score to qualify those?

We intend to eventually enable zkProofs for reviews, allowing people to anonymously review people with the qualifier of "Credibility score range," enabling reviews such as

"A highly credible person has negatively reviewed Bob"

Without the credibility score calculation, anonymous reviews lack any qualification to appropriately separate noise (spam from unreputable people) from signal.

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