Opinion diffusion is a crucial phenomenon in social networks, often underlying the way in which a collective of agents develops a consensus on relevant decisions. The voter model is a well-known theoretical model to study opinion spreading in social networks and structured populations. Its simplest version assumes that an updating agent will adopt the opinion of a neighboring agent chosen at random. The model allows us to study, for example, the probability that a certain opinion will fixate into a consensus opinion, as well as the expected time it takes for a consensus opinion to emerge. Standard voter models are oblivious to the opinions held by the agents involved in the opinion adoption process. We propose and study a context-dependent opinion spreading process on an arbitrary social graph, in which the probability that an agent abandons opinion $a$ in favor of opinion $b$ depends on both $a$ and $b$. We discuss the relations of the model with existing voter models and then derive theoretical results for both the fixation probability and the expected consensus time for two opinions, for both the synchronous and the asynchronous update models.

翻译：意见扩散是社会网络中的关键现象，通常决定了群体如何就相关决策达成共识。投票者模型是研究社会网络与结构化群体中意见传播的经典理论模型。其最简版本假设更新个体随机采纳邻居的意见。该模型可研究特定意见形成共识的概率及共识达成所需的预期时间。标准投票者模型不考虑意见采纳过程中涉及个体所持有的意见内容。我们提出并研究任意社会图上的上下文依赖意见扩散过程，其中个体放弃意见$a$转而采纳意见$b$的概率同时取决于$a$和$b$。我们探讨了该模型与现有投票者模型的关系，并针对同步和异步更新模型推导出两种意见的固定概率与预期共识时间的理论结果。