论文标题
在社交媒体上调节算法过滤
Regulating algorithmic filtering on social media
论文作者
论文摘要
通过过滤用户看到的内容，社交媒体平台可以影响用户的看法和决策，从他们的就餐选择到投票偏好。这种影响引起了审查，许多人呼吁对过滤算法进行法规，但是设计和执行法规仍然具有挑战性。在这项工作中，我们研究了三个问题。首先，鉴于法规，如何设计审核来执行它？其次，审核是否会在平台上施加性能成本？第三，审核如何激励平台过滤的内容？作为响应，我们提出了一种方法，即鉴于法规，审计师可以测试该调节是否仅符合Black-Box访问过滤算法。然后，我们转向平台的观点。该平台的目标是在满足监管时最大化目标功能。我们发现，在某些条件下，该法规不会在平台上施加高性能成本，尤其是，内容多样性可以在使平台和监管机构的利益保持一致方面发挥关键作用。
By filtering the content that users see, social media platforms have the ability to influence users' perceptions and decisions, from their dining choices to their voting preferences. This influence has drawn scrutiny, with many calling for regulations on filtering algorithms, but designing and enforcing regulations remains challenging. In this work, we examine three questions. First, given a regulation, how would one design an audit to enforce it? Second, does the audit impose a performance cost on the platform? Third, how does the audit affect the content that the platform is incentivized to filter? In response, we propose a method such that, given a regulation, an auditor can test whether that regulation is met with only black-box access to the filtering algorithm. We then turn to the platform's perspective. The platform's goal is to maximize an objective function while meeting regulation. We find that there are conditions under which the regulation does not place a high performance cost on the platform and, notably, that content diversity can play a key role in aligning the interests of the platform and regulators.
