Analysis of Terms of Service on Social Media Platforms: Consent Challenges and Assessment Metrics

TL;DR

This study evaluates how clearly social media platforms communicate user consent in their Terms of Service, revealing significant shortcomings in clarity, transparency, and interface design that hinder informed user agreement.

Contribution

It introduces a novel three-dimensional framework for assessing consent communication in ToS documents and applies it across major platforms, highlighting areas for improvement.

Findings

High linguistic complexity in ToS documents

Limited disclosure of data practices and retention

Absence of explicit interface commitments to granular consent

Abstract

Social media platforms typically obtain user consent through Terms of Service (ToS) presented at account creation, rather than through dedicated consent forms. This study investigates whether consent-related information is clearly communicated within these ToS documents. We propose and apply a three-dimensional consent evaluation framework encompassing Textual Accessibility, Semantic Transparency, and Interface Design as declared in ToS documents. Using a combination of computational and qualitative analyses, we assess ToS from 13 major social media platforms. Our findings reveal important shortcomings across platforms, including high linguistic complexity, widespread use of non-committal language, limited disclosure of data retention and sharing practices, and the absence of explicit interface-level commitments to granular or revocable consent. These results indicate that while consent is formally embedded in ToS, it is often presented in ways that constrain clarity and meaningful choice. Rather than treating ToS documents as informed consent instruments, this study positions them as consent-bearing documents whose design and content shape the conditions under which users are asked to agree to data practices. The proposed framework offers a systematic method for evaluating consent information within ToS in the absence of explicit consent forms and informs the design of clearer, more ethically robust consent mechanisms for data-intensive digital platforms.