Signed bounded confidence models for opinion dynamics.
C. Altafini and F. Ceragioli
Automatica, to appear, 2017.
The aim of this paper is to modify continuous-time bounded confidence opinion dynamics models so that ``changes
of opinion'' (intended as changes of the sign of the initial states) are never induced during the evolution.
Such sign invariance can be achieved by letting opinions of different sign localized near the origin interact
negatively, or neglect each other, or even repel each other.
In all cases, it is possible to obtain sign-preserving bounded confidence models with state-dependent
connectivity and with a clustering behavior similar to that of a standard bounded confidence model.