I'm currently in the process of getting my phd on this exact topic and I'm always happy to hear the problem of network interference in A/B tests being tackled at more and more tech companies. Here's a small (incomplete) list of (mainly industrial) references to solutions to this problem.
- Facebook data scientists have an extensive list of publications on the topic: [1][2]. (Dean Eckles is now at MIT).
- LinkedIn's experimentation team has also published papers on the topic: [3][4]
- Data scientists at Google have also worked on this topic. One external publication/collaboration I'm aware of is: [5]
- Facebook data scientists have an extensive list of publications on the topic: [1][2]. (Dean Eckles is now at MIT).
- LinkedIn's experimentation team has also published papers on the topic: [3][4]
- Data scientists at Google have also worked on this topic. One external publication/collaboration I'm aware of is: [5]
[1] http://www.pnas.org/content/113/27/7316
[2] https://arxiv.org/abs/1404.7530
[3] http://www.kdd.org/kdd2017/papers/view/detecting-network-eff...
[4] https://dl.acm.org/citation.cfm?doid=2783258.2788602
[5] http://proceedings.mlr.press/v51/basse16b.pdf
Disclaimer: this list is heavily biased by experiences I've had through collaborations/internships. I am an author on [3]. Edit: formatting.