Semantic Incompleteness in Privacy Policy Goals

Abstract

Companies that collect personal information online often maintain privacy policies that are required to accurately reflect their data practices and privacy goals. To be comprehensive and flexible for future practices, policies contain ambiguity that summarize practices over multiple types of products and business contexts. Ambiguity in data practice descriptions undermines policies as an effective way to communicate system design choices to users, and as a reliable regulatory mechanism. In this paper, we report an investigation to identify incompleteness by representing data practice descriptions as semantic frames. The approach is a grounded analysis to discover which data actions and semantic roles correspond are needed to construct complete data practice descriptions. Our results include 281 data action instances obtained from 202 manually annotated statements across five privacy policies. Therein, we identified 878 instances of 17 types of semantic roles. Incomplete data practice descriptions undermine user comprehension, and can affect the user's perceived privacy risk, which we measure using factorial vignette surveys. We observed that user perception of risk decreases when two roles are present in a statement: the condition under which a data action is performed, and the purpose for which the user's information is used.