Ethical Frameworks for Conducting Social Challenge Studies

TL;DR

This paper examines the ethical frameworks developed for medical challenge studies and considers how their principles might inform social research, to initiate discussion on formalizing ethical standards for social challenge studies and encourage long-term evaluation of potential harms.

Abstract

Computational social science research, particularly online studies, often involves exposing participants to the adverse phenomenon the researchers aim to study. Examples include presenting conspiracy theories in surveys, exposing systems to hackers, or deploying bots on social media. We refer to these as "social challenge studies," by analogy with medical research, where challenge studies advance vaccine and drug testing but also raise ethical concerns about exposing healthy individuals to risk. Medical challenge studies are guided by established ethical frameworks that regulate how participants are exposed to agents under controlled conditions. In contrast, social challenge studies typically occur with less control and fewer clearly defined ethical guidelines. In this paper, we examine the ethical frameworks developed for medical challenge studies and consider how their principles might inform social research. Our aim is to initiate discussion on formalizing ethical standards for social challenge studies and encourage long-term evaluation of potential harms.

Figures (2)

• Figure 1: Decision tree outlining steps in the social challenge study ethical framework. This decision tree supports researchers in systematically evaluating key ethical considerations when designing or reviewing social challenge studies. It outlines steps, including assessment of exposure risks, consent pathways, participant vulnerability, use of deception, and harm mitigation strategies. Drawing analytically on medical challenge frameworks, the tree is designed to guide ethical decision-making for studies involving bots, misinformation, platform interventions, honeypots, and other controlled-risk designs in digital environments.
• Figure 2: Decision tree outlining steps in the social challenge study ethical framework related to informed consent. This tree helps researchers assess how informed consent should be obtained, waived, or substituted in studies involving deception, public interactions, or group-level exposure. It highlights the role of terms of service, the feasibility of direct consent, the importance of debriefing when possible, and ethical oversight for waivers or documented ethical justification for waivers, where applicable. It supports researchers conducting studies in environments where traditional consent is difficult or impossible to implement.