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作 者:马雨萌[1,2] 黄金霞 王昉[1] 汤怡洁[3] 周子健[3] MA Yu-meng;HUANG Jin-xia;WANG Fang;TANG Yi-jie;ZHOU Zi-jian(National Science Library,Chinese Academy of Sciences,Beijing 100190,China;Department of Information Management,Peking University,Beijing 100871,China;Wuhan Library,Chinese Academy of Sciences,Wuhan 430071,China)
机构地区:[1]中国科学院文献情报中心,北京100190 [2]北京大学信息管理系,北京100871 [3]中国科学院武汉文献情报中心,湖北武汉430071
出 处:《情报科学》2022年第7期169-176,185,共9页Information Science
基 金:国家社会科学基金青年项目“科技政策大数据语义分析方法与决策支持研究”(20CTQ030)。
摘 要:【目的/意义】如何对海量科技政策文本进行有效的分析,是大数据时代科技政务资源再利用与支撑科学决策的关键问题,需要拓展目前政策服务平台的数据细粒度加工与深层分析的功能。【方法/过程】本文从政策分析服务的需求出发,设计面向政策定量研究问题的文本分析模型,提出了政策外部特征与内容要素的文本分析方法,研发了科技政策分析服务平台,支持用户从政策颁布特征、重点布局、政策工具、热点演进、政策衍生、机构合作等方面对目标领域科技政策文本进行分析。【结果/结论】以大数据政策领域的分析结果为例验证了平台的服务效果,为政策服务平台向深度分析与科学决策支撑的服务转型提供了实践参考。【创新/局限】本文提出了面向政策定量分析问题场景的科技政策服务平台架构,平台服务在多源数据融合与深度分析能力上有待进一步提升。【Purpose/significance】How to effectively analyze massive S&T policy texts is a key issue on reusing government S&T resources and supporting scientific decision-making in the era of big data.It is necessary to expand the functions of fine-grained data processing and deep analysis in current policy service platforms.【Method/process】Based on the demand of policy analysis service,this paper designs a text analysis model for policy quantitative research and puts forward an analysis method of external features and content elements for policy texts.This paper developed a service platform for S&T policy analysis which supports users to analyze S&T policies in the target field of policy promulgation characteristics,policy layout,policy tools,hot spots evolution,policy derivation and institutional cooperation relations.【Result/conclusion】Service effects of this platform are verified by taking analysis results of big data policies as an example.This paper provides a practical reference for the transformation to services of supporting in-depth analysis and scientific decision of policy service platforms.【Innovation/limitation】The framework of S&T policy service platform for policy quantitative analysis is proposed in this paper.However,platform services need to be further improved in multi-source data fusion and in-depth analysis.
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