Stick It to The Man: Correcting for Non-Cooperative Behavior of Subjects in Experiments on Social Networks

Authors: 

Kaleigh Clary, University of Massachusetts Amherst; Emma Tosch and Jeremiah Onaolapo, University of Vermont; David D. Jensen, University of Massachusetts Amherst

Abstract: 

A large body of research in network and social sciences studies the effects of interventions in network systems. Nearly all of this work assumes that network participants will respond to interventions in similar ways. However, in real-world systems, a subset of participants may respond in ways purposefully different than their true outcome. We characterize the influence of non-cooperative nodes and the bias these nodes introduce in estimates of average treatment effect (ATE). In addition to theoretical bounds, we empirically demonstrate estimation bias through experiments on synthetically generated graphs and a real-world network. We demonstrate that causal estimates in networks can be sensitive to the actions of non-cooperative members, and we identify network structures that are particularly vulnerable to non-cooperative responses.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@inproceedings {277126,
title = {Stick It to The Man: Correcting for {Non-Cooperative} Behavior of Subjects in Experiments on Social Networks},
booktitle = {31st USENIX Security Symposium (USENIX Security 22)},
year = {2022},
address = {Boston, MA},
url = {https://www.usenix.org/conference/usenixsecurity22/presentation/clary},
publisher = {USENIX Association},
month = aug,
}