Recommendation systems are pervasive in the digital economy. An important assumption in many deployed systems is that user consumption reflects user preferences in a static sense: users consume the content they like with no other considerations in mind. However, as we document in a large-scale online survey, users do choose content strategically to influence the types of content they get recommended in the future. We model this user behavior as a two-stage noisy signalling game between the recommendation system and users: the recommendation system initially commits to a recommendation policy, presents content to the users during a cold start phase which the users choose to strategically consume in order to affect the types of content they will be recommended in a recommendation phase. We show that in equilibrium, users engage in behaviors that accentuate their differences to users of different preference profiles. In addition, (statistical) minorities out of fear of losing their minority content exposition may not consume content that is liked by mainstream users. We next propose three interventions that may improve recommendation quality (both on average and for minorities) when taking into account strategic consumption: (1) Adopting a recommendation system policy that uses preferences from a prior, (2) Communicating to users that universally liked ("mainstream") content will not be used as basis of recommendation, and (3) Serving content that is personalized-enough yet expected to be liked in the beginning. Finally, we describe a methodology to inform applied theory modeling with survey results.

翻译：推荐系统在数字经济中无处不在。许多已部署系统的一个重要假设是，用户消费以静态方式反映用户偏好：用户仅消费他们喜欢的内容，而不考虑其他因素。然而，正如我们在大规模在线调查中所记录的，用户确实会策略性地选择内容，以影响他们未来被推荐的内容类型。我们将这种用户行为建模为推荐系统与用户之间的两阶段噪声信号博弈：推荐系统初始承诺一种推荐策略，在冷启动阶段向用户呈现内容，用户则策略性地消费这些内容，以影响他们在推荐阶段将被推荐的内容类型。我们证明，在均衡状态下，用户会采取加剧其与不同偏好特征用户差异的行为。此外，（统计意义上的）少数群体因担心失去少数内容曝光机会，可能不会消费主流用户喜欢的内容。接着，我们提出三种考虑策略性消费后可能提升推荐质量（包括平均水平和针对少数群体）的干预措施：（1）采用基于先验偏好的推荐策略；（2）向用户说明普遍受喜爱的（“主流”）内容不会作为推荐依据；（3）在初始阶段提供足够个性化且预期会被喜欢的内容。最后，我们描述了一种结合调查结果指导应用理论建模的方法。