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

Emma Hoes, K. Jonathan Klueser, Fabrizio Gilardi

TL;DR

The paper addresses the challenge of studying digital communication given restricted data access and ethical constraints, and presents VIRENA, a no-code, open-source platform that combines realistic feed- and chat-based interfaces with live participants and configurable AI agents. It enables controlled experimentation across platform types, including configurable moderation and scripted content, under a template-driven, reproducible framework that preserves institutional data control. The authors detail the architecture, current capabilities, and a roadmap for 2026, highlighting use cases in research, education, and public communication, as well as ethical considerations and limitations. Overall, VIRENA offers a versatile infrastructure to study human–AI interaction, moderation effects, and deliberation in realistic social contexts, potentially accelerating evidence-based insights across disciplines.

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.

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

TL;DR

The paper addresses the challenge of studying digital communication given restricted data access and ethical constraints, and presents VIRENA, a no-code, open-source platform that combines realistic feed- and chat-based interfaces with live participants and configurable AI agents. It enables controlled experimentation across platform types, including configurable moderation and scripted content, under a template-driven, reproducible framework that preserves institutional data control. The authors detail the architecture, current capabilities, and a roadmap for 2026, highlighting use cases in research, education, and public communication, as well as ethical considerations and limitations. Overall, VIRENA offers a versatile infrastructure to study human–AI interaction, moderation effects, and deliberation in realistic social contexts, potentially accelerating evidence-based insights across disciplines.

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.
Paper Structure (39 sections, 1 figure, 5 tables)