English

VIRENA: Virtual Arena for Research, Education, and Democratic Innovation

Human-Computer Interaction 2026-02-19 v2 Artificial Intelligence Social and Information Networks

Abstract

Digital platforms shape how people communicate, deliberate, and form opinions. Studying these dynamics has become increasingly difficult due to restricted data access, ethical constraints on real-world experiments, and limitations of existing research tools. VIRENA (Virtual Arena) is a platform that enables controlled experimentation in realistic social media environments. Multiple participants interact simultaneously in realistic replicas of feed-based platforms (Instagram, Facebook, Reddit) and messaging apps (WhatsApp, Messenger). Large language model-powered AI agents participate alongside humans with configurable personas and realistic behavior. Researchers can manipulate content moderation approaches, pre-schedule stimulus content, and run experiments across conditions through a visual interface requiring no programming skills. VIRENA makes possible research designs that were previously impractical: studying human--AI interaction in realistic social contexts, experimentally comparing moderation interventions, and observing group deliberation as it unfolds. Built on open-source technologies that ensure data remain under institutional control and comply with data protection requirements, VIRENA is currently in use at the University of Zurich and available for pilot collaborations. Designed for researchers, educators, and public organizations alike, VIRENA's no-code interface makes controlled social media simulation accessible across disciplines and sectors. This paper documents its design, architecture, and capabilities.

Keywords

Cite

@article{arxiv.2602.12207,
  title  = {VIRENA: Virtual Arena for Research, Education, and Democratic Innovation},
  author = {Emma Hoes and K. Jonathan Klueser and Fabrizio Gilardi},
  journal= {arXiv preprint arXiv:2602.12207},
  year   = {2026}
}

Comments

VIRENA is under active development and currently in use at the University of Zurich. This preprint will be updated as new features are released. For the latest version and to inquire about demos or pilot collaborations, contact the authors