@inproceedings{tan-etal-2026-said,
title = "He Said, She Said, They Simulated: Simulating Situated Gossip with {LLM} Agents",
author = "Tan, Yicong and
Shen, Yun and
Zhang, Yang",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.emnlp-main.1618/",
pages = "36763--36806",
ISBN = "979-8-89176-459-0",
abstract = "Gossip has been investigated primarily through vignette-based surveys, which provide limited insights into the dynamic and adaptive gossip behaviors within real-world contexts. To address these limitations, we introduce an LLM agent-based simulation framework, designed as a configurable experimental laboratory for gossip research. We validate our framework across three core dimensions of gossip dynamics: initiation, reaction, and perception. Our framework can reproduce several behavioral trends observed in human studies and enable analysis of agents' reasoning and temporally unfolding interactions. We further augment the framework with a chain-of-reasoning mechanism to support exploratory investigation, demonstrating how explicit agent reasoning and experiment-level controllability enable the generation of hypotheses about gossip dynamics beyond fixed survey settings. Overall, our framework bridges LLM-based computational modeling and social science, complementing vignette-based methodologies and enabling controlled, systematic study of complex social behaviors. Our code is available at: https://github.com/TrustAIRLab/Gossip-Simulacra."
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<abstract>Gossip has been investigated primarily through vignette-based surveys, which provide limited insights into the dynamic and adaptive gossip behaviors within real-world contexts. To address these limitations, we introduce an LLM agent-based simulation framework, designed as a configurable experimental laboratory for gossip research. We validate our framework across three core dimensions of gossip dynamics: initiation, reaction, and perception. Our framework can reproduce several behavioral trends observed in human studies and enable analysis of agents’ reasoning and temporally unfolding interactions. We further augment the framework with a chain-of-reasoning mechanism to support exploratory investigation, demonstrating how explicit agent reasoning and experiment-level controllability enable the generation of hypotheses about gossip dynamics beyond fixed survey settings. Overall, our framework bridges LLM-based computational modeling and social science, complementing vignette-based methodologies and enabling controlled, systematic study of complex social behaviors. Our code is available at: https://github.com/TrustAIRLab/Gossip-Simulacra.</abstract>
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%0 Conference Proceedings
%T He Said, She Said, They Simulated: Simulating Situated Gossip with LLM Agents
%A Tan, Yicong
%A Shen, Yun
%A Zhang, Yang
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-459-0
%F tan-etal-2026-said
%X Gossip has been investigated primarily through vignette-based surveys, which provide limited insights into the dynamic and adaptive gossip behaviors within real-world contexts. To address these limitations, we introduce an LLM agent-based simulation framework, designed as a configurable experimental laboratory for gossip research. We validate our framework across three core dimensions of gossip dynamics: initiation, reaction, and perception. Our framework can reproduce several behavioral trends observed in human studies and enable analysis of agents’ reasoning and temporally unfolding interactions. We further augment the framework with a chain-of-reasoning mechanism to support exploratory investigation, demonstrating how explicit agent reasoning and experiment-level controllability enable the generation of hypotheses about gossip dynamics beyond fixed survey settings. Overall, our framework bridges LLM-based computational modeling and social science, complementing vignette-based methodologies and enabling controlled, systematic study of complex social behaviors. Our code is available at: https://github.com/TrustAIRLab/Gossip-Simulacra.
%U https://aclanthology.org/2026.emnlp-main.1618/
%P 36763-36806
Markdown (Informal)
[He Said, She Said, They Simulated: Simulating Situated Gossip with LLM Agents](https://aclanthology.org/2026.emnlp-main.1618/) (Tan et al., EMNLP 2026)
ACL