Understanding Website Privacy Policies—A Longitudinal Analysis Using Natural Language Processing

Abstract

Privacy policies are the main method for informing Internet users of how their data are collected and shared. This study aims to analyze the deficiencies of privacy policies in terms of readability, vague statements, and the use of pacifying phrases concerning privacy. This represents the undertaking of a step forward in the literature on this topic through a comprehensive analysis encompassing both time and website coverage. It characterizes trends across website categories, top-level domains, and popularity ranks. Furthermore, studying the development in the context of the General Data Protection Regulation (GDPR) offers insights into the impact of regulations on policy comprehensibility. The findings reveal a concerning trend: privacy policies have grown longer and more ambiguous, making it challenging for users to comprehend them. Notably, there is an increased proportion of vague statements, while clear statements have seen a decrease. Despite this, the study highlights a steady rise in the inclusion of reassuring statements aimed at alleviating readers’ privacy concerns.

A User-Centered Privacy Policy Management System for Automatic Consent on Cookie Banners

“…The use of these technologies for the same purpose is explored in [25]. Deficiencies of policies in terms of readability and ambiguity are evaluated in [26], while [27] investigates how language technologies can support users in better understanding these policies. In [28], machine learning-based strategies for automating GDPR compliance checks in data processing agreements are introduced.…”