In recent years, major events, such as wars and political tensions, have occurred in rapid succession. Naturally, most events are complex and can be interpreted in different ways, which spawns the question of how to actually integrate different viewpoints in event-centric knowledge graphs (ECKGs). One way is to limit the validity of statements to respective viewpoints, which allows for the representation of conflicting information in ECKGs without causing ontological inconsistencies. To consistently fuse such statements in queries or reasoning processes, a viewpoint model deciding whether two given viewpoints are compatible has to exist. Prior work utilized viewpoint hierarchies to describe aggregations of stances between different groups; yet, in the real world, viewpoints of individuals and groups are usually formed by complex mutual influences that cannot be captured by simple hierarchical models. To cater for such influences, in this paper we propose influence networks as a novel viewpoint model based on opinion dynamics for ECKGs. In contrast to simple hierarchical aggregations, our model captures fine-grained social interactions between different agents enabling the inference of stances towards claims. To illustrate the effectiveness of our model in practical applications, we conduct extensive simulation studies to compare the model with established results in social physics and provide a case study to contrast our model to viewpoint hierarchies for ECKGs.