基于现实行为数据的开源设计社区仿真模型研究

Open source design community simulation model research based on behavior data

由于开源设计社区规模较大、社交网络复杂、用户行为多样等,针对用户实施的管理策略通常难以通过常识进行预判,为决策制定的科学性带来挑战。通过分析开源设计社区用户行为特征和社区特点,以社区用户历史行为数据以及由其构成的复杂社会网络等真实数据作为输入参数,基于复杂适应系统理论构建了开源设计社区的多主体仿真模型。通过使用基于现实数据的输入参数,对开源设计社区进行了多次动态仿真,结果证实了该多主体仿真模型对开源设计社区模拟的有效性,从而为开源设计社区科学管理和优化奠定了基础。

Owing to the complex factors of open source design community such as large-scale community, complex social network and variable user behavior, a scientific decision hard be formulated. Through the analysis of open source design community s user behavior characteristics and community characteristics, a multi-agent simulation model was built with a series of community user behavior history data and social network data. By using the input parameters based on real data, the dynamic simulation of open source design community was carried out. Simulation results confirmed the validity of the multi-agent simulation model. The research could lay the foundation for open source design community s scientific management and optimization.