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：观点扩散是社会网络中的一个关键现象，通常决定了群体如何在相关决策上达成共识。选民模型是研究社会网络和结构化群体中观点传播的著名理论模型。其最简单的版本假设更新代理会随机选择邻居的观点进行采纳。该模型允许我们研究，例如，某种观点固化为共识观点的概率，以及共识观点出现所需的预期时间。标准选民模型忽视了参与观点采纳过程的代理所持的观点。我们提出并研究了一种在任意社交图上的情境依赖观点扩散过程，其中代理放弃观点\\(a\\)转而支持观点\\(b\\)的概率取决于\\(a\\)和\\(b\\)两者。我们讨论了该模型与现有选民模型的关系，然后推导了同步和异步更新模型下两种观点的固定概率和期望共识时间的理论结果。