Placebo Effect of Control Settings in Feeds Are Not Always Strong
Silas Hsu, Vinay Koshy, Kristen Vaccaro, Christian Sandvig, Karrie Karahalios
Abstract
Recent work has catalogued a variety of "dark" design patterns, including deception, that undermine user intent. We focus on deceptive "placebo" control settings for social media that do not work. While prior work reported that placebo controls increase feed satisfaction, we add to this body of knowledge by addressing possible placebo mechanisms, and potential side effects and confounds from the original study. Knowledge of these placebo mechanisms can help predict potential harms to users and prioritize the most problematic cases for regulators to pursue. In an online experiment, participants (N=762) browsed a Twitter feed with no control setting, a working control setting, or a placebo control setting. We found a placebo effect much smaller in magnitude than originally reported. This finding adds another objection to use of placebo controls in social media settings, while our methodology offers insights into finding confounds in placebo experiments in HCI.
• Human-centered computing → HCI theory, concepts and models; User studies; Empirical studies in HCI .
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext d16cb375-2d29-43cf-af84-83114dec7c0bCited by top-tier papers2
- PaperTok: Exploring the Use of Generative AI for Creating Short-form Videos for Research CommunicationMeziah Ruby Cristobal, Hyeonjeong Byeon, Tze-Yu Chen, Ruoxi Shang et al.CHI 2026 · 2 citations
- Better Assumptions, Stronger Conclusions: The Case for Ordinal Regression in HCIBrandon Victor Syiem, Eduardo VellosoCHI 2026 · 1 citation
Builds on6
- What Makes a Dark Pattern... Dark?: Design Attributes, Normative Considerations, and Measurement MethodsArunesh Mathur, Mihir Kshirsagar, Jonathan R. MayerCHI 2021 · 327 citations
- "It's a scavenger hunt": Usability of Websites' Opt-Out and Data Deletion ChoicesHana Habib, Sarah Pearman, Jiamin Wang, Yixin Zou et al.CHI 2020 · 113 citations
- About Engaging and Governing Strategies: A Thematic Analysis of Dark Patterns in Social Networking ServicesThomas Mildner, Gian-Luca Savino, Philip R. Doyle, Benjamin R. Cowan et al.CHI 2023 · 82 citations
- "AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AIAgnes Mercedes Kloft, Robin Welsch, Thomas Kosch, Steeven VillaCHI 2024 · 32 citations
- Mapping the Design Space of Teachable Social Media Feed ExperiencesK. J. Kevin Feng, Xander Koo, Lawrence Tan, Amy S. Bruckman et al.CHI 2024 · 20 citations
Related papers
- A Systematic Review of User Experiments on the Effects of Dark PatternsBrennan Schaffner, Luis Heysen, Marshini ChettyCHI 2026 · 2 citations
- A Comparative Study of How People With and Without ADHD Recognise and Avoid Dark Patterns on Social MediaThomas Mildner, Daniel Fidel, Evropi Stefanidi, Pawel W. Wozniak et al.CHI 2025 · 13 citations
- Awareness, Navigation, and Use of Feed Control Settings OnlineSilas Hsu, Kristen Vaccaro, Yin Yue, Aimee Rickman et al.CHI 2020 · 18 citations
- UI Dark Patterns and Where to Find Them: A Study on Mobile Applications and User PerceptionLinda Di Geronimo, Larissa Braz, Enrico Fregnan, Fabio Palomba et al.CHI 2020 · 262 citations
- From Awareness to Action: Exploring End-User Empowerment Interventions for Dark Patterns in UXYuwen Lu, Chao Zhang, Yuewen Yang, Yaxing Yao et al.CSCW 2024 · 30 citations
