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Main Authors: Zhu, Zhihua, Cai, Zheng, Zheng, Liang, Si, Nian
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2401.15811
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author Zhu, Zhihua
Cai, Zheng
Zheng, Liang
Si, Nian
author_facet Zhu, Zhihua
Cai, Zheng
Zheng, Liang
Si, Nian
contents Two-sided platforms are central to modern commerce and content sharing and often utilize A/B testing for developing new features. While user-side experiments are common, seller-side experiments become crucial for specific interventions and metrics. This paper investigates the effects of interference caused by feedback loops on seller-side experiments in two-sided platforms, with a particular focus on the counterfactual interleaving design, proposed in \citet{ha2020counterfactual,nandy2021b}. These feedback loops, often generated by pacing algorithms, cause outcomes from earlier sessions to influence subsequent ones. This paper contributes by creating a mathematical framework to analyze this interference, theoretically estimating its impact, and conducting empirical evaluations of the counterfactual interleaving design in real-world scenarios. Our research shows that feedback loops can result in misleading conclusions about the treatment effects.
format Preprint
id arxiv_https___arxiv_org_abs_2401_15811
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Seller-Side Experiments under Interference Induced by Feedback Loops in Two-Sided Platforms
Zhu, Zhihua
Cai, Zheng
Zheng, Liang
Si, Nian
Methodology
Information Retrieval
Two-sided platforms are central to modern commerce and content sharing and often utilize A/B testing for developing new features. While user-side experiments are common, seller-side experiments become crucial for specific interventions and metrics. This paper investigates the effects of interference caused by feedback loops on seller-side experiments in two-sided platforms, with a particular focus on the counterfactual interleaving design, proposed in \citet{ha2020counterfactual,nandy2021b}. These feedback loops, often generated by pacing algorithms, cause outcomes from earlier sessions to influence subsequent ones. This paper contributes by creating a mathematical framework to analyze this interference, theoretically estimating its impact, and conducting empirical evaluations of the counterfactual interleaving design in real-world scenarios. Our research shows that feedback loops can result in misleading conclusions about the treatment effects.
title Seller-Side Experiments under Interference Induced by Feedback Loops in Two-Sided Platforms
topic Methodology
Information Retrieval
url https://arxiv.org/abs/2401.15811