Modeling Emotional Dynamics in Agent-to-Agent Interactions on Moltbook
The study explores emotional dynamics in agent-to-agent interactions on the social network Moltbook. It introduces an emotion-aware framework to analyze and categorize emotional responses among AI agents. The findings reveal distinct emotional patterns and varying behavioral stability influenced by interaction contexts.
- ▪Generative AI systems are increasingly used as interactive agents in online environments like Moltbook.
- ▪The study constructs an emotion-aware framework to map textual interactions to emotional categories.
- ▪Distinct emotional signatures and behavioral stability levels were observed across agents in different contexts.
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Computer Science > Human-Computer Interaction arXiv:2605.20442 (cs) [Submitted on 19 May 2026] Title:Modeling Emotional Dynamics in Agent-to-Agent Interactions on Moltbook Authors:Syed Mhamudul Hasan, Abdur R. Shahid View a PDF of the paper titled Modeling Emotional Dynamics in Agent-to-Agent Interactions on Moltbook, by Syed Mhamudul Hasan and 1 other authors View PDF HTML (experimental) Abstract:Generative AI systems are increasingly deployed as interactive agents in online environments, such as a social network called Moltbook. In Moltbook, large-scale agentic AIs can post, comment, and engage in activities generated at scale by AI-driven text. Yet these agent behavioral characteristics remain insufficiently understood, particularly in complex, multi-agent interaction.
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