摘要
随着Web 2.0的在线知识社区(Online Knowledge Community,OKC)中的用户不断进行知识的个体建构和社会建构,在社区中形成了社会系统和知识系统,而这两个系统不同层面间如何进行交互序化,目前学术界还未进行这方面的系统探索。基于自组织与复杂适应系统理论,从两个系统的微观层面出发,本文构建了OKC中社会系统与知识系统不同层面交互序化的假设。选取OKC的典型代表Wikipedia中词条数据作为研究样本,使用向量自回归(vector autoregression,VAR)模型对社会系统与知识系统的不同层面交互序化的假设进行了检验。研究结果表明,社会系统的微观层面对知识系统的中观层面和宏观层面存在显著的交互影响,知识系统的微观层面对社会系统的宏观层面存在显著影响。本文拓展了OKC系统序化的现有研究,为OKC平台建设和管理提供了实践启示。
In the Web2.0 era,users in the Online Knowledge Community(OKC)have formed social and knowledge systems individually as well as socially.The interaction of these two systems has become a concern for the OKC platform.Based on the theories of self-organization and complex adaptive systems,this paper constructs a collaborative order model of social and knowledge system at a level different from the micro-level of the two systems.In this paper,we use Wikipedia,a representative OKC,as a research platform,and apply the vector autoregression(VAR)method to construct four interactive interaction models among the different levels.The research results show that the micro-level of the social system has a significant interactive effect on the meso-level and macro-level of the knowledge system,and the micro-level of the knowledge system has a significant impact on the macro-level of the social system.This study enhances the existing research on OKC system ordering,and at the same time provides inspiration for the OKC platform construction and management process.
作者
裘江南
蔡承杰
杨畅
李岩
Qiu Jiangnan;Cai Chengjie;Yang Chang;Li Yan(School of Economics and Management,Dalian University of Technology,Dalian 116024)
出处
《情报学报》
CSSCI
CSCD
北大核心
2021年第5期435-447,共13页
Journal of the China Society for Scientific and Technical Information
基金
国家自然科学基金“在线知识社区人机协作模式及对知识社会建构影响研究”(72074044)
“在线知识社区中社会系统与知识系统协同序化机制和规律研究”(71573030)
辽宁省社科联项目“重大突发公共卫生事件恐慌情绪引导研究”(2021lslybkt-028)
中央高校基本科研基金“在线社区人与机器人协作机制研究”(DUT20RW207)。
关键词
在线知识社区
交互序化
社会系统
知识系统
VAR
Online Knowledge Community(OKC)
collaborative order
social system
knowledge system
vector autoregression(VAR)
