大数据时代下网络群体智能研究方法

Research Method of Web Collective Intelligence in Era of Big Data

首先,对大数据时代下大众广泛深度交互的互联网环境进行了分析;其次,提出并释义了网络群体智能,指出网络群体智能具有"网络数据驱动,交互形式复杂,网络效应强大,知识生产为主,不确定性认知"等特性;然后,提出网络群体智能研究方法,该研究方法以复杂性科学方法论为指导,坚持融贯论,以复杂性科学、网络化数据挖掘和不确定性人工智能为支撑理论方法,突出网络群体智能特色和多学科交叉融合研究,采用系统分析、建模分析和仿真分析相结合技术途径从结构和动力学视角对网络群体智能科学问题进行多尺度多层次研究,解决网络群体智能研究理论方法不足的问题,深化了对网络群体智能和社会计算的认识。

Firstly, the internet environment in the era of big data where the crowds interact adequately each other was analyzed. Secondly, the concept of web collective intelligence was put forward and explained, and its characteristics involving network data driven, complex interaction form, strong network effect, knowledge production dominated and cognition with uncertainty were ob-tained, then the research paradigm of web collective intelligence was put forward, the method with complexity science methodolo-gy as the guidance adheres to syncretism, took complexity science, networked data mining and artificial intelligence with uncer-tainty as backbone theory and method, outstood web collective intelligence characteristic and interdisciplinary research, and ap-plied a technique with a combination of system analysis, modeling analysis and simulation analysis to study the scientific problems of web collective intelligence from multi-scale and multi-level perspective, which solves the deficiency problem of the research theories and methods of web collective intelligence and deepens the knowledge of web collective intelligence and social computing.