Understanding and Empowering Intelligence Analysts: User-Centered Design for Deepfake Detection Tools
Y. Kelly Wu, Saniat Javid Sohrawardi, Candice R. Gerstner, Matthew Wright
2025Year
7Citations
3Top-tier citations
Abstract
organize analytics Figure 1: Study flow showing the two phases of user studies: the Requirements Study, followed by the Ontology Study and their sub-steps.
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Install the CLIlune papers fulltext 39b55d0f-404b-434a-bc85-a5723bb69420Cited by top-tier papers3
- Seeing, Hearing, and Knowing Together: Multimodal Strategies in Deepfake Videos DetectionChen Chen, Dion GohCHI 2026 · 2 citations
- Collab: Fostering Critical Identification of Deepfake Videos on Social Media via Synergistic AnnotationShuning Zhang, Linzhi Wang, Shixuan Li, Yuanyuan Wu et al.CHI 2026 · 1 citation
- "Create an environment that protects women, rather than selling anxiety!": Participatory Threat Modelling with Chinese Young Women Living AloneShijing He, Chenkai Ma, Chi Zhang, Adam D. G. Jenkins et al.CHI 2026 · 1 citation
Builds on6
- FaceForensics++: Learning to Detect Manipulated Facial ImagesAndreas Rössler, Davide Cozzolino, Luisa Verdoliva, Christian Riess et al.ICCV 2019 · 2,966 citations
- The Utility of Explainable AI in Ad Hoc Human-Machine TeamingRohan R. Paleja, Muyleng Ghuy, Nadun Ranawaka Arachchige, Reed Jensen et al.NeurIPS 2021 · 103 citations
- Putting Tools in Their Place: The Role of Time and Perspective in Human-AI Collaboration for Qualitative AnalysisJessica L. Feuston, Jed R. BrubakerCSCW 2021 · 89 citations
- Dungeons & Deepfakes: Using scenario-based role-play to study journalists' behavior towards using AI-based verification tools for video contentSaniat Javid Sohrawardi, Y. Kelly Wu, Andrea Hickerson, Matthew WrightCHI 2024 · 21 citations
- Face X-Ray for More General Face Forgery DetectionLingzhi Li, Jianmin Bao, Ting Zhang, Hao Yang et al.CVPR 2020
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