How trust and distrust shape influence in social networks
Joint Trust-Distrust Structure Shapes Belief Propagation and Collective Dynamics
Social and Information Networks
Summary
People spread beliefs through their social networks based on whom they trust or distrust. This paper studies how trust and distrust affect the way opinions form and change in groups. The authors create a model that considers trust and distrust together to see how they influence whether people agree or disagree overall. They find that how trust and distrust relate changes who has influence and how groups reach consensus or remain divided. They also introduce a way to measure how comfortable people feel with their social connections, linking relationships to group beliefs.
What this means in practice
- •For social media platform designers: Improve algorithms to identify influential users by modeling how trust and distrust jointly impact opinion spread in online networks.
- •For organizational behavior analysts: Better predict how trust and distrust relationships affect group consensus and decision-making in teams and organizations.
Authors
Mozhgan Khanjanianpak, Yu-Ru Lin
Abstract
Belief propagation in social networks depends on how trust and distrust jointly shape interpersonal influence. We develop a network model that treats trust and distrust as distinct but statistically coupled quantities. Their joint values determine the net trust and uncertainty of each relationship, and a neighbor can influence an agent only when both threshold conditions are satisfied. We show that the correlation between trust and distrust reshapes the transition between consensus and fragmentation by changing the availability of influential neighbors. Network connectivity also affects this transition, whereas degree heterogeneity has a more limited effect when networks have comparable mean degree. Moreover, the availability of influential neighbors alone does not determine the final consensus: correlations between relational properties and network degree can select agents with different degree compositions, altering the direction and magnitude of collective belief. Finally, we introduce a comfort index that quantifies the expected availability of influential neighbors and analytically links the joint trust-distrust structure to collective dynamics. Our results establish a mechanistic connection between relational structure, effective social influence, and emergent collective belief states.