Agent-based simulations show recommender logic sets visibility regimes, with popularity-based systems creating reinforcement loops that concentrate exposure while collaborative filtering distributes it broadly, and network structure modulates creator inequality.
Winecoff, and Arvind Narayanan
2 Pith papers cite this work. Polarity classification is still indexing.
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Marketplace Evaluation uses repeated-interaction simulations to assess information access systems with marketplace-level metrics such as retention and market share that complement traditional accuracy measures.
citing papers explorer
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Joint Effects of Recommender Systems and Network Structure on the Visibility of Content and Creators
Agent-based simulations show recommender logic sets visibility regimes, with popularity-based systems creating reinforcement loops that concentrate exposure while collaborative filtering distributes it broadly, and network structure modulates creator inequality.
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Evaluation of Agents under Simulated AI Marketplace Dynamics
Marketplace Evaluation uses repeated-interaction simulations to assess information access systems with marketplace-level metrics such as retention and market share that complement traditional accuracy measures.