mlsanityData to 14 Oct 2026

Multi-Agent Systems Shape Social Norms for Prosocial Behavior Change

arXiv 2602.07433 ↗First posted 7 Feb 2026cs.HC cs.AI cs.CYcited by 1

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Abstract (arXiv)

Social norm interventions are used promote prosocial behaviors by highlighting prevalent actions, but their effectiveness is often limited in heterogeneous populations where shared understandings of desirable behaviors are lacking. This study explores whether multi-agent systems can establish "virtual social norms" to encourage donation behavior. We conducted an online experiment where participants interacted with a group of agents to discuss donation behaviors. Changes in perceived social norms, conformity, donation behavior, and user experience were measured pre- and postdiscussion. Results show that multi-agent interactions effectively increased perceived social norms and donation willingness. Notably, in-group agents led to stronger perceived social norms, higher conformity, and greater donation increases compared to out-group agents. Our findings demonstrate the potential of multi-agent systems for creating social norm interventions and offer insights into leveraging social identity dynamics to promote prosocial behavior in virtual environments.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 49 references that are in the map. First posted on arXiv 7 Feb 2026.

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6 of 49 references.

References · 6

  1. 2019Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Goodcited by 209
  2. 2020Effects of Persuasive Dialogues: Testing Bot Identities and Inquiry Strategiescited by 29
  3. 2024ComPeer: A Generative Conversational Agent for Proactive Peer Supportcited by 24
  4. 2023ChoiceMates: Supporting Unfamiliar Online Decision-Making with Multi-Agent Conversational Interactionscited by 22
  5. 2024Multi-Agents are Social Groups: Investigating Social Influence of Multiple Agents in Human-Agent Interactionscited by 16
  6. 2024Antisocial Analagous Behavior, Alignment and Human Impact of Google AI Systems: Evaluating through the lens of modified Antisocial Behavior Criteria by Human Interaction, Independent LLM Analysis, and AI Self-Reflectioncited by 1

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