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, Isma\"el Jecker, and Jakub Svoboda, "Simplified Game of Life: Algorithms and Complexity", 45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020)]
翻译:个人的社会关系对个人意见(主题、产品或其他任何方面)的影响是一个众所周知的现象,已经对此进行了广泛研究。本文认为这是一个正面(即信任)或消极(不信任)社会关系网络,其中每个人最初(对主题、产品或其他任何方面)都持有正面或负面(对主题、产品或任何方面)意见,这种观点随着时间、时间、时间、因邻居的影响而发生变化而发生变化。在这里,一个受信任的邻居的影响与邻居的意见是一致的,而一个不受信任的计算机邻居的影响与邻居的意见是一致的,而一个不受信任的邻居的专题讨论会的影响则与邻居的科学意见相反。这一扩展的抽象介绍了基于当地门槛的见解动态,并在陈述了在这种环境中,当个人根据大多数邻居的意见改变其观点时,产生的一些自然可及性问题的计算复杂性之后,证明在意见配置数量上有一个上限,即根据任何这种模型的对称性正数-只关系网络变化,在网络规模上是多式的。