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文章主要探讨了开放数据研究主题知识结构演化的判断条件、知识结构的演化过程以及产生知识结构演化的环境变迁。通过对数似然值来确定高频关键词在不同时间维度是否发生极显著性变化来测度知识结构是否发生演化;通过因子分析和社会网络分析来揭示知识结构的演化过程;通过定性分析总结知识结构演化的原因。研究结果发现,首先,对数似然值是一种测度知识结构发生演化的判断方法。其次,开放数据研究主题知识结构的演化过程:由数据共享向数据挖掘、开放获取、关联数据过渡,并逐渐向电子政务、隐私保护、开放政府数据、开放数据政策研究转换。第三,开放数据研究主题知识结构演化是同开放数据的环境变迁相关联的,即开放数据经历的项目驱动转向技术驱动过渡到政策驱动的发展过程。
The article mainly discusses the judgment conditions, the evolution of knowledge structure and the changes of environment that cause the evolution of knowledge structure. Through the logarithmic likelihood value to determine high-frequency key words in different time dimensions whether significant changes occur to measure whether the evolution of knowledge structure; through factor analysis and social network analysis to reveal the evolution of knowledge structure; through qualitative analysis of knowledge The reason for the evolution of the structure. The results show that, first of all, log-likelihood is a measure to measure the evolution of knowledge structure. Secondly, the evolution of the theme knowledge structure of open data research: the transition from data sharing to data mining, open access and related data, and gradually to the e-government, privacy protection, open government data, open data policy research and conversion. Third, the evolution of the theme of open data research is related to the environmental changes in open data. That is, the project driven by open data has shifted from technology-driven to policy-driven development.