本文结合实证案例探讨如何以社会计算研究社会系统中的涌现现象。中国风险投资产业的案例说明VC投资行为与产业网络结构共演过程中的正反馈导致了“精英俱乐部型小世界网络”的结构涌现，解释了个体行为如何促成集体涌现；某大型科技公司的案例展现了集体智能涌现的过程及因素，并说明了系统转型前后团队创新能力的影响因素存在差异，解释了非线性发展对员工行为的影响。案例体现了调查数据与大数据结合、多种社会计算方法综合运用的方法取向及其在复杂系统研究中应用的可行性。

Through empirical case studies, this paper aims to explore how social computing can be used to study emergent phenomena in social systems. The case of Chinas venture capital (VC) industry demonstrates how positive feedback between VC investment behavior and industry network structure leads to the emergence of a "small world network with an elite clique". This explains how individual actions contribute to collective emergence. The case of a large technology company illustrates the evolution process of team innovation and the factors behind the emergence of a teams high innovative ability. Additionally, it demonstrates differences in factors influencing the innovation capabilities of internal subsystems before and after systemic transformation, shedding light on the impact of non linear development on employee behavior. These cases highlight the feasibility of combining survey data with big data and employing various social computing methods in complex system research.

感谢清华大学计算社会科学与国家治理实验室以及腾讯研究项目“基于QQ大数据意见领袖识别研究”（20182001706）的资助。

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