DynamiX: Large-Scale Dynamic Social Network Simulator
Yanhui Sun, Wu Liu, Wentao Wang, Hantao Yao, Jiebo Luo, Yongdong Zhang

TL;DR
DynamiX is a large-scale social network simulator that models dynamic relationships and user behaviors, improving attitude evolution simulation and offering new insights into follower growth and opinion leader development.
Contribution
It introduces a novel dynamic social network modeling framework with modules for core agent selection and relationship strategies, addressing the gap in evolving social relationships.
Findings
Enhanced simulation of attitude evolution and collective behaviors.
Improved accuracy in modeling dynamic social relationships.
Provides empirical evidence for opinion leader cultivation.
Abstract
Understanding the intrinsic mechanisms of social platforms is an urgent demand to maintain social stability. The rise of large language models provides significant potential for social network simulations to capture attitude dynamics and reproduce collective behaviors. However, existing studies mainly focus on scaling up agent populations, neglecting the dynamic evolution of social relationships. To address this gap, we introduce DynamiX, a novel large-scale social network simulator dedicated to dynamic social network modeling. DynamiX uses a dynamic hierarchy module for selecting core agents with key characteristics at each timestep, enabling accurate alignment of real-world adaptive switching of user roles. Furthermore, we design distinct dynamic social relationship modeling strategies for different user types. For opinion leaders, we propose an information-stream-based link…
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