Social-media platforms are one of the most prevalent communication media today. In such systems, a large amount of content is generated and available to the platform. However, not all content can be transmitted to every possible user at all times. At the other end are the users, who have their own preferences about which content they enjoy, which is often unknown ex ante to the platform. We model the interaction between the platform and the users as a signaling game with asymmetric information, where each user optimizes its preference disclosure policy, and the platform optimizes its information disclosure policy. We provide structural as well as existence of policies that constitute Bayesian Nash Equilibria, and necessary optimality conditions used to explicitly compute the optimal policies.

翻译：社交媒体平台是当今最普遍的传播媒介之一。在此类系统中，平台会生成并获取大量内容。然而，并非所有内容都能在任何时刻传输给每一位潜在用户。另一方面，用户对自身喜好的内容具有各自的偏好，而这些偏好通常无法被平台事先获知。我们将平台与用户之间的互动建模为具有非对称信息的信号博弈，其中每个用户优化其偏好披露策略，平台则优化其信息披露策略。我们给出了构成贝叶斯纳什均衡的策略结构及其存在性证明，并提供了用于显式计算最优策略的必要最优性条件。