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Data visualization explorations
Graduates
Bri Mai
BS in Interaction Design — Interaction DesignCourse:
Data Visualization
Faculty:
Santiago Lombeyda
Term:
2026 Fall
Collaborators:
Keller Yang, Silvia Zhang
Sniffo: Social media credibility detection tool
Sniffo is a social media misinformation, AI-generated content, and author risk detection tool designed for everyday users. Built as an iOS app with a Dynamic Island integration, Sniffo runs passively in the background while users scroll — alerting them to suspicious posts without disrupting their experience, and offering deeper in-app analysis for those who want to dig further. The tool uses data visualization to make complex detection results legible and approachable.
Process:
In a team of 3 designers, I steered the design strategy and interaction system while collaborating on ideation and visual direction. We started by scoping the two most critical use cases: passive detection during scroll, and an extended in-app report for users who wanted deeper analysis. The core UX tension was alerting users without pulling them out of their scroll — the Dynamic Island solved that. We built out the detection category framework, mapped datasets to UI states, and iterated on the in-app glyph interaction system to make multi-variable results (misinformation, AI generation, author risk) scannable at a glance.
Learning Outcomes:
Sniffo pushed me to think seriously about trust as a design material — how you present uncertain or algorithmic information to users without either alarming them or lulling them into false confidence. Designing for misinformation detection meant every UI decision had an ethical dimension: how much to explain, how to visualize risk without being reductive, and how to keep the tool feeling approachable.
Project Website: