Generalized Reputation Computation Ontology and Temporal Graph Architecture

TL;DR

This paper proposes a generalized reputation system based on a temporal weighted liquid rank algorithm, supporting liquid democracy principles, to enhance trust and reduce manipulation in social, financial, and marketplace environments.

Contribution

It introduces a novel reputation computation ontology and a temporal graph architecture with an incremental reputation design, validated on real social and blockchain data.

Findings

System effectively models reputation in social and financial networks.

Reputation scores demonstrate robustness against manipulation.

Framework supports multi-agent AI evolution.

Abstract

The problem of reliable democratic governance is important for survival of any community, and it will be more critical over time communities with levels of social connectivity in society rapidly increasing with speeds and scales of electronic communication. In order to face such challenge, different sorts of rating and reputation systems are being developed, however reputation gaming and manipulation in such systems appears to be serious problem. We are considering use of advanced reputation system supporting "liquid democracy" principle with generalized design and underlying ontology fitting different sorts of environments such as social networks, financial ecosystems and marketplaces. The suggested system is based on "temporal weighted liquid rank" algorithm employing different sorts of explicit and implicit ratings being exchanged by members of the society. For the purpose, we suggest "incremental reputation" design and graph database used for implementation of the system. Finally, we present evaluation of the system against real social network and financial blockchain data. The entire framework is expected to be the foundation of any multi-agent AI framework, so the evolution of distributed multi-agent AI architecture and dynamics will be based on the organic reputation scores earned by the agents that are part of it.