With a Little Help From My Friends: Collective Manipulation in Risk-Controlling Recommender Systems
Recommendation systems have become central gatekeepers of online information, shaping user behaviour across a wide range of activities. In response, users increasingly organize and coordinate to steer algorithmic outcomes toward diverse goals, such as promoting relevant content or limiting harmful material, relying on platform affordances -- such as likes, reviews, or ratings. While these mechanisms can serve beneficial purposes, they can also be leveraged for adversarial manipulation, particularly in systems where such feedback directly informs safety guarantees. In this paper, we study this vulnerability in recently proposed risk-controlling recommender systems, which use binary user fe...
| Authors | Giovanni De Toni, Cristian Consonni, Erasmo Purificato et al. |
|---|---|
| Primary category | cs.IR |
| Published | 30 March 2026 |
| Last updated at source | 30 March 2026 |
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