Comparing Design Metaphors and User-Driven Metaphors for Interaction Design

Abstract

Metaphors enable designers to communicate their ideal user experience for platforms. Yet, we often do not know if these design metaphors match users' actual experiences. In this work, we compare design and user metaphors across three different platforms: ChatGPT, Twitter, and YouTube. We build on prior methods to elicit 554 user metaphors, as well as ratings on how well each metaphor describes users' experiences. We then identify 21 design metaphors by analyzing each platform's historical web presence since their launch date. We find that design metaphors often do not match the metaphors that users use to describe their experiences. Even when design and user metaphors do match, the metaphors do not always resonate universally. Through these findings, we highlight how comparing design and user metaphors can help to evaluate and refine metaphors for user experience.

Figures (4)

• Figure 1: Twitter's about page in the first quarter of 2016. To identify design metaphors, we utilized the WayBack Machine to view the home and about pages of platforms from their launch date until 2024. We collected screenshots of both pages on the first day of the first and third quarter, when available. Next, we looked for [PLATFORM] is [METAPHOR] statements to identify design metaphors.
• Figure 2: The user metaphor elicitation process. We extend prior sentence completion methods to elicit users' metaphors for their experiences with platforms. After removing invalid metaphors, we use the elicited metaphors to understand the experiences of a broader pool of participants.
• Figure 3: The average ratings for how reflective users found each user metaphor. We surveyed a broader, additional pool of participants to understand how reflective user metaphors' were of other users' experiences. Participants rated the reflectivity of metaphors on a 5-point Likert scale, with one being not well and five being extremely well. We average these ratings (approximately 50 ratings per metaphor) and indicate user metaphors that match or are related to design metaphors. We find that metaphors that contain explicit or related keywords from design metaphors are a mixed bag when it comes to how well they reflect users' experiences.
• Figure 4: The first author and an independent annotator worked to group similar experiences described across design metaphors and the metaphors with average ratings in the top quartile. We include codes for the surfaced design metaphors and the most common codes for the top quartile of user metaphors for each platform (codes that apply to 5 or more user metaphors). The full set of codes for the top quartile of user metaphors are included in the supplementary material.