# Researchers find intuitive prompts improve LLM social media simulation

Digest AI · Research · published 2026-09-28T04:00:00Z

Canonical: https://digestai.news/story/researchers-find-intuitive-prompts-improve-llm-social-media-simulation

## Summary

A new study on arXiv tested how well language models simulate individual reactions to social media posts. Researchers profiled eight Serbian participants through questionnaires, interviews, and self-presentations. They then asked four language models to predict those reactions under five different prompt conditions, varying profile content and instruction style.

The study found that attitudinal content improved prediction accuracy over demographic backstories. Agents aligned more closely with their assigned profiles than participants did with their own survey answers. Prompts instructing models to respond intuitively and immediately—rather than analytically—yielded the highest fidelity. This method reduced the compression of individual differences and performed best on unfamiliar topics, suggesting these agents could serve as general-purpose simulated users.

## Key points

- Eight Serbian participants profiled via questionnaires, interviews, and self-presentations
- Four language models tested under five prompt conditions for social media reaction prediction
- Intuitive prompts improved fidelity, especially on unfamiliar topics, per arXiv study

## Why it matters

Better simulation of individual social media behavior could improve platform testing and reduce risks of AI-driven manipulation before elections.

## Sources

1. [Thinking Less to Simulate Better: Intuitive Prompting Improves LLM Agents Simulating Individual Social Media Reactions, Including Unfamiliar Content](https://arxiv.org/abs/2609.30563) (arXiv cs.AI, 2026-09-28, primary source)

## Cite

Digest AI, "Researchers find intuitive prompts improve LLM social media simulation", 28 September 2026, https://digestai.news/story/researchers-find-intuitive-prompts-improve-llm-social-media-simulation

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