我国数据要素政策主题演化与识别分析
Analysis of the Evolution and Identification of Topics in China's Data Element Policies
苏婉 1于森 1禚传阳1
作者信息
- 1. 吉林大学商学与管理学院 长春 130012
- 折叠
摘要
[目的/意义]直面数据要素特征复杂性及外部不确定性不断叠加的环境,亟须分析我国数据要素政策发展重点,掌握其演化趋势和区域主题,对于推动数据要素领域发展具有重要意义.[方法/过程]选取我国31个省(市、自治区)的597份数据要素政策文本,划分6个阶段和4个区域,从时间和空间两个维度采用DTM模型和LDA模型分别对其进行主题演化分析和区域主题识别.[结果/结论]研究发现,不同阶段各个主题强度随时间演进发生变化,同一主题不同阶段关键词也有所不同,归纳总结3条主要的主题演化路径;不同区域数据要素政策在重点领域上存在差异,但在推动数据要素发展方面政策导向和落地举措存在相似之处.通过对我国数据要素政策主题演化与识别分析,以期更好把握我国数据要素政策发展脉络,为数据要素领域有序发展提供有力支撑.
Abstract
[Purpose/Significance]Facing the environment where the complexity of data element charac-teristics and the external uncertainty are constantly superimposed,it is urgent to analyze the key development trend of China's data element policy,and grasp its evolution trends and regional topics,which is of great sig-nificance for promoting the development of the data element industry.[Method/Process]This study focused on a sample of 597 policy texts on data elements from the 31 provinces(municipalities,autonomous regions)in China.These texts were categorized into six stages and four regions,and analyzed in terms of temporal and spatial dimensions using the DTM model and the LDA model to explore the topic evolution and identify regional topics,respectively.[Result/Conclusion]The study finds that the intensity of each topic at different stages changes over time,and the keywords of the same topic are different at different stages,and summarizes three major topic evolution paths.Data element policies in different regions are different in the focus areas,but there are similarities in the policy orientation and landing initiatives in promoting the development of data elements.Through the analysis of topic evolution and identification of data element policies in China,it aims to provide the better understanding of the data element policy development and offer strong support for the or-derly development of the data element field.
关键词
数据要素/政策分析/主题演化/主题识别Key words
data element/policy analysis/topic evolution/topic identification引用本文复制引用
出版年
2024
NETL
NSTL
万方数据