Opinion Evolution among friends and foes: the deterministic Majority Rule - extended abstract
Miriam Di Ianni

TL;DR
This paper studies opinion dynamics in social networks with positive and negative relationships, introducing a local threshold model, analyzing computational complexity, and providing bounds on the evolution of opinions in such networks.
Contribution
It introduces a local threshold-based opinion model with mixed trust/distrust relationships and proves polynomial bounds on the number of opinion configurations in symmetric positive-only networks.
Findings
Computational complexity of reachability problems is established.
Polynomial upper bound on opinion configurations in symmetric positive networks.
Generalizes previous results on opinion dynamics and network evolution.
Abstract
The influence of the social relationships of an individual on the individual's opinions (about a topic, a product, or whatever else) is a well known phenomenon and it has been widely studied. This paper considers a network of positive (i.e. trusting) or negative (distrusting) social relationships where every individual has an initial positive or negative opinion (about a topic, a product, or whatever else) that changes over time, at discrete time-steps, due to the influences each individual gets from its neighbors. Here, the influence of a trusted neighbor is consistent with the neighbor's opinion, while the influence of an untrusted neighbor is opposite to the neighbor's opinion. This extended abstract introduces the local threshold-based opinion dynamics and, after stating the computational complexity of some natural reachability problems arising in this setting when individuals…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Game Theory and Applications · Complex Network Analysis Techniques
