A/B testing is an effective way to assess the potential impacts of two treatments. For A/B tests conducted by IT companies, the test users of A/B testing are often connected and form a social network. The responses of A/B testing can be related to the network connection of test users. This paper discusses the relationship between the design criteria of network A/B testing and graph cut objectives. We develop asymptotic distributions of graph cut objectives to enable rerandomization algorithms for the design of network A/B testing under two scenarios.
@article{arxiv.2309.08797,
title = {On the Asymptotics of Graph Cut Objectives for Experimental Designs of Network A/B Testing},
author = {Qiong Zhang},
journal= {arXiv preprint arXiv:2309.08797},
year = {2023}
}