On Capturing the Narrative: Social Media Manipulation Wargaming for Cyberliteracy

2026-07-27

AI Summary

This study addresses the limitations of traditional digital literacy education in countering generative AI–driven disinformation, which often lacks immersive, adversarial training. To bridge this gap, the authors designed and deployed “Capture the Narrative,” a four-week multi-institutional competition that introduced red-teaming–style social media manipulation exercises into digital literacy curricula. Student teams employed large language models to create social bots and influence a simulated society of 4,000 AI-driven non-player characters on a custom platform replicating real-world platform incentives and large-scale interactions. The inaugural iteration engaged 108 teams from 18 universities, generating over 7 million posts—60% of the platform’s content. However, surveys revealed no significant improvement in students’ ability to detect bots, indicating that high engagement alone does not enhance discernment and underscoring the need for more refined experiential designs in digital literacy interventions.

Abstract

Misinformation is deeply embedded in online discourse, with nearly one in five posts during global events generated by bots that amplify false content. In recent years, the use of Generative AI has further lowered the barrier to producing convincing misinformation, yet most digital literacy education still relies on static checklists and single-player inoculation games built for an earlier media landscape. This paper describes how we addressed this educational gap through Capture the Narrative, a four-week multi-university competition in which student teams build LLM-powered bots to influence a simulated election. We report on our custom social-media platform, the competition environment and design of its 4,000 AI-driven Non-Player Character (NPC) citizens, and what running Capture the Narrative at scale actually involved. In our first iteration, 108 teams from 18 Australian universities produced 7,068,206 player-bot posts, approximately 60% of all platform content. We surveyed 256 students before and 83 after the competition to understand their perceptions of misinformation and the game itself and found that students did not become more confident at spotting bots, contrary to what inoculation theory predicts. Because engagement was rewarded, most teams prioritised high-volume posting over nuanced influence, mirroring real-world platform dynamics. We close with recommendations for educators considering similar interventions, and propose future improvements, such as including a blue-team defensive phase.

Problem

• misinformation
• generative AI
• cyberliteracy
• social media manipulation
• digital literacy education

Innovation

• Generative AI
• LLM-powered bots
• social media simulation
• cyberliteracy education
• misinformation wargaming