Trust based attachment
Julian Kates-Harbeck, Martin A. Nowak

TL;DR
This paper introduces Trust Based Attachment (TBA), a social network generation algorithm grounded in trust, gossip, and reputation dynamics, which replicates key properties of real-world social networks.
Contribution
The paper proposes TBA, a novel algorithm for generating social networks based on trust and gossip, explaining the role of social information spread in network formation.
Findings
TBA produces networks with high clustering, small-world properties, and power-law degree distributions.
TBA can be approximated by simple friend-of-friend routines based on triadic closure.
The work links trust, gossip, and social information spread to the formation of social ties.
Abstract
In social systems subject to indirect reciprocity, a positive reputation is key for increasing one's likelihood of future positive interactions. The flow of gossip can amplify the impact of a person's actions on their reputation depending on how widely it spreads across the social network, which leads to a percolation problem. To quantify this notion, we calculate the expected number of individuals, the "audience", who find out about a particular interaction. For a potential donor, a larger audience constitutes higher reputational stakes, and thus a higher incentive, to perform "good" actions in line with current social norms. For a receiver, a larger audience therefore increases the trust that the partner will be cooperative. This idea can be used for an algorithm that generates social networks, which we call trust based attachment (TBA). TBA produces graphs that share crucial…
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Taxonomy
TopicsComplex Network Analysis Techniques · Opinion Dynamics and Social Influence · Evolutionary Game Theory and Cooperation
