Emergence in complex social systems: an analysis of structure and action coevolution through big data

Abstract

Abstract This paper examines several empirical case studies to explore how social computing can be used to study emergent phenomena in social systems. A case study of China’s 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” phenomenon, explaining how individual action contributes to collective emergence. The case of a large technology company illustrates the evolution of team innovation and the factors behind the emergence of its high levels of innovation. Additionally, this case 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 essentially highlight the feasibility of combining survey data with big data as well as the viability in employing various social computing methods in complex system research.