From TikTok to Telegram: Cross-Platform Efficacy and User Acceptance of Erroneous and Flawless Misinformation Interventions

要旨

Misinformation interventions are often evaluated under ideal conditions, yet real-world systems are rarely flawless. We report on an online experiment ($N=1,004$) comparing five state-of-the-art interventions -- inoculation, accuracy prompt, community note, fact-check, and indicators -- across TikTok, Telegram, and X. We examined efficacy and user perceptions under flawless and erroneous implementations. Misinformation accompanied by fact-checks and indicators was rated as significantly less accurate, while community notes showed weaker effects. Modality did not significantly influence intervention efficacy and had only minor effects on user acceptance. Community notes, fact-checks, and indicators were rated as more helpful but also more annoying than the less informative accuracy prompts. Notably, the efficacy of interventions disappeared under erroneous conditions. This highlights the crucial role of intervention quality in fostering trust and acceptance. Our findings provide (1) a cross-platform evaluation of interventions and (2) empirical evidence that accuracy and reliability are crucial in complex social media environments.

著者
Katrin Hartwig
Technische Universität Darmstadt, Darmstadt, Germany
Tom Biselli
Science and Technology for Peace and Security (PEASEC), Technical University of Darmstadt, Darmstadt, Germany
Franziska Schneider
Technical University of Darmstadt, Darmstadt, Germany
Immanuel Lamp
Technical University of Darmstadt, Darmstadt, Germany
Christian Reuter
Technical University of Darmstadt, Darmstadt, Germany

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Social Media

P1 - Room 132
7 件の発表
2026-04-16 18:00:00
2026-04-16 19:30:00