Scrollytelling as an Alternative Format for Privacy Policies

TL;DR

It is suggested that scrollytelling can preserve comprehension while enhancing the experience of policy reading, and improve user experience over text, yielding higher engagement, lower cognitive load, greater willingness to adopt the format, and increased perceived clarity.

Abstract

Privacy policies are long, complex, and rarely read, which limits their effectiveness in informed consent. We investigate scrollytelling, a scroll-driven narrative approach, as a privacy policy presentation format. We built a prototype that interleaves the full policy text with animated visuals to create a dynamic reading experience. In an online study (N=454), we compared our tool against text, two nutrition-label variants, and a standalone interactive visualization. Scrollytelling improved user experience over text, yielding higher engagement, lower cognitive load, greater willingness to adopt the format, and increased perceived clarity. It also matched other formats on comprehension accuracy and confidence, with only one nutrition-label variant performing slightly better. Changes in perceived understanding, transparency, and trust were small and statistically inconclusive. These findings suggest that scrollytelling can preserve comprehension while enhancing the experience of policy reading. We discuss design implications for accessible policy communication and identify directions for increasing transparency and user trust.

Figures (10)

• Figure 1: Storyboard of our scrollytelling interface, showing representative moments of the narrative: (A) full-text policy, (B) animation stage, (C) vertical progress bar signaling that scrolling can continue, (D) introduction of inferred personal attributes or interests, (E) synchronized highlighting of the corresponding clause in the textual policy, (F & G) enumeration and clustering of data items, (H) visualization of data ingestion, and (I) depiction of sharing flows to third-party actors. See Section \ref{['sec:system:scrollytelling']} for a full annotated description of the interface.
• Figure 2: Annotated view of the interactive summary visualization. (A) Actors are displayed in rows, sorted by the volume of data they receive. (B) Hovering over a rectangle reveals the associated data type and its sharing destinations. (C) Clicking a rectangle scrolls and highlights the corresponding passages in the full-text policy. (D) When multiple references exist, a navigation aid allows cycling through them. (E) A search bar enables filtering of data items by keyword. Rectangles use color and pattern to encode both the category of data and the certainty of collection or sharing.
• Figure 3: Sketches from the first participatory design workshop. Without being primed on narrative structures, participants explored diverse ways of visually communicating privacy policy content. Ideas included hierarchical outlines, metaphors such as food and gardening, conversational formats, and user prompts. Some focused on summarizing key sections (a, d), while others proposed interaction scenarios or analogies for how data is used and shared (b, c). These early sketches helped us surface user expectations, preferences, and concerns, which informed the overall framing and scope of our tool.
• Figure 4: Sketches from the second participatory design workshop. Participants were primed with examples of scrollytelling narratives and asked to sketch how privacy policies might be explained using similar formats. Three of the four sketches are centered around a user avatar.
• Figure 5: Demographic makeup of our study participants.