| 动态关联子群信息熵视域下智慧政府信息协同度测度研究 |
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| 引用本文： | 胡漠,马捷,郝志远.动态关联子群信息熵视域下智慧政府信息协同度测度研究[J].情报理论与实践,2021(2):96-102,82. |
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| 作者姓名： | 胡漠 马捷 郝志远 |
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| 作者单位： | 吉林大学管理学院;吉林大学信息资源中心 |
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| 基金项目： | 国家社会科学基金重点项目“信息生态视角下智慧城市信息协同结构与模式研究”的成果,项目编号:17ATQ007。 |
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| 摘 要： | 目的/意义]文章旨在明确我国智慧政府各部门间的信息协同度,为相关决策者明确我国智慧政府信息协同网络结构优化过程中的发力点提供依据。方法/过程]采用命名实体识别与社会网络分析的方法,获取现阶段我国智慧政府信息协同网络结构数据,并以此为数据源,运用动态关联子群信息熵算法,对我国智慧政府不同部门间的信息协同度进行测度,并对测度结果进行分析与可视化。结果/结论]研究结果可获得智慧政府中每两个不同政府部门间信息协同度的强弱分布。研究结果表明:中国智慧政府信息协同网络中,国家发展和改革委员会节点与国务院节点间的信息协同度最大,国务院节点与财政部节点间的信息协同度次之,国家发展和改革委员会节点与财政部节点再次之。局限]由于研究精力与论文篇幅有限,本研究仅对智慧政府信息协同度进行了研究,尚未在此基础上对如何预测与引流智慧政府不同部门间信息协同的信息量进行研究。
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| 关 键 词： | 动态关联子群信息熵算法 智慧政府 信息协同 信息熵 信息测度 |
Research on the Information Collaboration Degree of Smart Government under the Perspective of Dynamic Association Subgroup Information Entropy |
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| Abstract: | Purpose/significance]The purpose of this paper is to ascertain the information collaborative degree among the various departments of Chinese smart government,which can provide the bases for the relevant decision makers to clarify the starting points in the optimization process of the smart government information collaborative network structure.Method/process]This paper used the methods of named entity recognition and social network analysis to obtain the data of smart government information collaborative network structure,which was treated as the data source.Simultaneously,the paper used the dynamic association subgroups information entropy algorithm to measure the information collaborative degree among different departments of Chinese smart government,and analyzed and visualized the information collaborative results.Result/conclusion]The research result of this paper is to obtain the strength-weakness distribution of information collaborative degree between any two different smart government departments.And the result shows that the information collaborative degree between the National Development and Reform Commission node and the State Council node is the largest,the second is the information collaborative degree between the State Council node and the Ministry of Finance node,and the third is the information collaborative degree between the National Development and Reform Commission node and the Ministry of Finance node.Limitations]Due to the restrictions of the research effort and the paper length,this paper has only studied the information collaborative degree of Chinese smart government,and has not studied how to predict and distribute the amount of information collaboration between any two different smart government departments. |
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| Keywords: | dynamic association subgroups information entropy algorithm smart government information collaboration information entropy information measurement |
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