Octan Network


Game-changing Innovation for the Web3 World.

The Challenges

Reputation is a fundamental concept that has been central to our social interactions for centuries. It refers to the collective beliefs or opinions held by others about a person or entity, and it can have a significant impact on trust, credibility, and success, especially in the digital world.
With the rapid growth of the Web3 industry, which involves millions of users, transactions, and wallet addresses operating in a decentralized manner, measuring the specific reputation of an entity has become increasingly important.
This is where Octan’s Reputation Ranking System comes into play.

What is Reputation Ranking System?

Octan's Reputation Ranking System (RRS) is a powerful engine that uses advanced mathematical ranking algorithms to accurately calculate the reputation scores of users and other entities within the Web3 ecosystem. RRS utilizes well-established PageRank algorithms in combination with several pairwise ranking algorithms (e.g. HodgeRank, personalized and online learning), modified and improved by Octan Labs to fit the on-chain data analytics context.
It draws inspiration from Google's PageRank and is built on the extensive research and publications (since 2019) of Paven Do, founder of Octan Labs.
See more here.

How the Reputation Ranking System works

The RRS captures user activities and behaviors via on-chain records: transactions, contract interactions, transactional volume, and gas spent; providing a universal, comparative, and quantitative measurement of the reputation of accounts within communities and the entire space.
By analyzing graphs of transactions recorded on chains, the RRS employs sophisticated algorithms to calculate the reputation scores of accounts, making it a highly valuable metric for measuring and tracking social insights in the dynamic and rapidly evolving Web3 ecosystem.
From the transaction graph, we can induce:
  • Total Degree: number of oriented (directed) connections of an account with others. Total degree = in_degree + out_degree
  • Total In_degree: number of IN-connections of an account (IN-transfers from others to the account)
  • Total Out_degree: number of OUT-connections of an account (OUT-transfers from the account to others)
E.g: in Fig.1, nodes (accounts) A, B, C, D, E, F have:
Fig.1: A simple visualization for PageRank
(many transactions with the same direction add up to 1 degree)

Octan Ranking Intuitions

  • The reputation score of a public address (or account) is the probability of a random unbiased account interacting with that address at any given moment in an infinite random interaction.
  • More IN-transfers or Indegree (receiving value), then higher reputation score
  • IN-transfers from a high reputation account result in greater reputation score than receiving from a low reputation account
  • OUT-transfers or Outdegree (sending value) result in a lower reputation score.
  • Considering age-weight, value weight: latest transactions are more meaningful than the old ones, greater priced value transactions are better.
  • Preventing Sybil attack, manipulation, sinkage effect
In Fig.1, node B receives the most in-transfers, thus having the highest score. Nodes A and C both receive one in-transfer but C has a higher score because its in-transfer is from B, the highest-scored node. The smallest nodes mean the lowest scores because they have NO in-transfer (or indegree).

Applications of the Reputation Ranking System

We are proud to expand the capabilities of the Reputation Ranking System (RRS), which provides Reputation Scoring & Analysis Services such as the Reputation Board and Reputation Analytics. By leveraging new data sources and advanced analytics tools, the RRS delivers valuable insights about entities within the Web3 ecosystem. Also, projects and marketing agencies can use reputation scores and reputation ranking board to classify and qualify, to segment users and audiences in Web3 space.
Learn more about Reputation Board:
Learn more about Reputation Analytics:
Investors can use the RRS for risk assessment and fraud detection, while researchers and analysts can identify emerging trends and opportunities in the Web3 space. The RRS also enables project owners and communities to create qualified communities by leveraging member reputation scores for voting and other decision-making or governance processes.
The potential of the RRS goes beyond the Web3 ecosystem. It has the power to unleash DeFi and DAO, as well as promote the adoption of Web3 applications, then create a more reliable and sustainable token-based economy for everyone.