CoSimRec: New Framework Measures Coordinated Content Penetration in Recommender Feedback Loops
Researchers introduce CoSimRec, an offline agent-based evaluation framework designed to model the interplay between coordinated accounts, dynamic ranking, and user responses in recommender system feedback loops. The framework proposes the Algorithmic Penetration Rate (APR) metric family to quantify the extent to which target content reaches and engages non-bot users. Experiments across multiple datasets show that popularity-based and feedback-sensitive ranking algorithms can significantly increase coordinated content penetration, while synchronization-aware ranking strategies can mitigate this effect.
Why it matters: This work offers a systematic approach to evaluating how recommender systems may amplify coordinated content, addressing a critical gap in robustness assessments.
Full story at: arXiv Information Retrieval ↗