论计算社会科学的双重功能

Dual Function of Computational Social Science

计算社会科学是由技术驱动的社会研究新路径,侧重于用计算方法探究社会关系和社会互动中的模式。与传统社会科学相比,认知上,这一新路径依仗基于自主体模型的生成解释能够帮助人们更好地理解社会的复杂现象,而利用大数据和机器学习等技术,重复预言的可靠性也得以提高;实践上,它可以克服以往社会治理策略的一些缺陷,也有助于设计更美好的未来。不过,在作出新颖预言方面,计算社会科学亦有自身的局限。

Computational social science is a technology-driven approach to social studies, which focuses on the exploration of patterns in social relations and social interactions by using the computational method. Contrary to traditional social sciences, in cognition, this new approach can help better understand the complex phenomena of society by the generative explanation based on the agent-based modeling while the reliability of repetitive prediction can be improved by means of big data and machine learning. In practice, this approach can overcome some defects in previous strategies of social governance and help design a better human future. However, computational social science also has its limitations in novel prediction.