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 change their opinions according to the opinions of the majority of their neighbors, proves an upper bound on the number of opinion configurations met by a symmetric positive-only relationships network evolving according to any of such models, which is polynomial in the size of the network. This generalizes a result in [Krishnendu Chatterjee, Rasmus Ibsen-Jensen, Ismaël Jecker, and Jakub Svoboda, "Simplified Game of Life: Algorithms and Complexity", 45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020)]