Web privacy is experienced via two public artifacts: site utterances in policy texts, and the actions users are required to take during consent interfaces. In the extensive cross-section audits we've studied, there is a lack of longitudinal data detailing how these artifacts are changing together, and if interfaces are actually doing what they promise in policy. ConsentDiff provides that longitudinal view. We build a reproducible pipeline that snapshots sites every month, semantically aligns policy clauses to track clause-level churn, and classifies consent-UI patterns by pulling together DOM signals with cues provided by screenshots. We introduce a novel weighted claim-UI alignment score, connecting common policy claims to observable predicates, and enabling comparisons over time, regions, and verticals. Our measurements suggest continued policy churn, systematic changes to eliminate a higher-friction banner design, and significantly higher alignment where rejecting is visible and lower friction.

翻译：网络隐私体验通过两个公开载体呈现：网站政策文本中的声明，以及用户在同意界面中必须执行的操作。在我们研究的大量横截面审计中，缺乏详细描述这些载体如何共同变化、以及界面是否真正履行政策承诺的纵向数据。ConsentDiff 提供了这一纵向视角。我们构建了一个可复现的流水线，每月对网站进行快照，通过语义对齐政策条款以追踪条款级变动，并通过整合 DOM 信号与截图提供的线索对同意界面模式进行分类。我们引入了一种新颖的加权声明-界面对齐评分方法，将常见政策声明与可观测谓词关联起来，支持跨时间、地区和垂直领域的比较。我们的测量结果表明：政策持续变动、系统性调整消除了高摩擦横幅设计，且在拒绝选项可见且摩擦较低的情况下对齐度显著更高。