摘要
数字化时代下,使用大数据来表征世界已成为认知社会和研究人类行为的重要方式。大数据在方法、原则与步骤上承袭传统归纳实证主义方法论,在技术创新上又有所超越,但其未能弥补传统方法论的先天不足,自身又深陷于算法的实践构架与哲学意义探讨中。从归纳实证主义方法论出发,以明晰大数据在现代研究中的定位与角色,考察大数据参与科学研究和知识生产的可行性,确认其作为一种方法模式与技术工具可运用至科学研究中,提出大数据知识生产优化路径,从而推进大数据的理论研究与实践应用。
In the digital age,the representation of the world by big data has been an important method to know the society and study human behaviors.In terms of its methods,principles and procedures,big data adopts traditional inductive positivism methodology.Although big data excels in technological innovation,it fails to compensate for its congenital deficiency in traditional inductive methodology,and it is deeply involved in the exploration of practical framework and philosophical implications of algorithm.Starting with the inductive positivism methodology,the paper clarifies the position and role of big data in modern knowledge production,and verifies its feasibility in scientific research and knowledge production.As a method and technology,big data can be applied to scientific research.The paper also proposes optimized paths for big data knowledge production in order to push forward the theoretical research and practical application of big data.
作者
李琳
LI Lin(School of Humanities,Tongji University,Shanghai 200092,China)
出处
《太原理工大学学报（社会科学版）》
2020年第3期75-80,共6页
Journal of Taiyuan University of Technology(Social Science Edition)
关键词
归纳实证
大数据
知识生产
inductive positivism
big data
knowledge production
