LLM digital twin simulates short-video platform policy changes

Researchers have developed an LLM-augmented digital twin designed to simulate and evaluate policy changes on short-video platforms. This system uses a modular four-twin architecture (User, Content, Interaction, Platform) to model the complex co-evolution of platform policies, creator incentives, and user behavior. By integrating LLMs for tasks like persona generation and trend prediction, the digital twin enables reproducible experimentation with both traditional and AI-driven policies, offering a way to study their long-term impacts in a controlled environment. AI

IMPACT Provides a framework for studying the impact of AI-driven policies on platform dynamics and user behavior.

RANK_REASON The cluster contains a research paper detailing a novel methodology for policy evaluation using LLMs and digital twins. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• Haoting Zhang
• LLM
• short-video platforms

• paper
• product
• other

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →