The anatomy of a Web of Trust: the Bitcoin-OTC market

TL;DR

This paper studies the structure and dynamics of a reputation web of trust in the Bitcoin-OTC marketplace using multilayer network analysis, revealing how rewarding and punitive behaviors influence reputation and user classifications.

Contribution

It introduces a multilayer network approach to analyze reputation dynamics, distinguishing rewarding and punitive behaviors and their impact on user reputation in a peer-to-peer cryptocurrency marketplace.

Findings

Rewarding and punitive behaviors have similar topological properties.

Reputation results from complex interactions of different behaviors.

Identifies three user classes: trustworthy, untrusted, controversial.

Abstract

Bitcoin-otc is a peer to peer (over-the-counter) marketplace for trading with bit- coin crypto-currency. To mitigate the risks of the p2p unsupervised exchanges, the establishment of a reliable reputation systems is needed: for this reason, a web of trust is implemented on the website. The availability of all the historic of the users interaction data makes this dataset a unique playground for studying reputation dynamics through others evaluations. We analyze the structure and the dynamics of this web of trust with a multilayer network approach distin- guishing the rewarding and the punitive behaviors. We show that the rewarding and the punitive behavior have similar emergent topological properties (apart from the clustering coefficient being higher for the rewarding layer) and that the resultant reputation originates from the complex interaction of the more regular behaviors on the layers. We show which are the behaviors that correlate (i.e. the rewarding activity) or not (i.e. the punitive activity) with reputation. We show that the network activity presents bursty behaviors on both the layers and that the inequality reaches a steady value (higher for the rewarding layer) with the network evolution. Finally, we characterize the reputation trajectories and we identify prototypical behaviors associated to three classes of users: trustworthy, untrusted and controversial.