| 我国智慧政府信息协同网络结构识别与分析 |
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| 引用本文： | 胡漠,马捷,张云开,武博.我国智慧政府信息协同网络结构识别与分析[J].情报学报,2020,39(1):47-56. |
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| 作者姓名： | 胡漠 马捷 张云开 武博 |
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| 作者单位： | 吉林大学管理学院,长春 130022;吉林大学管理学院,长春 130022;吉林大学信息资源中心,长春 130022;早稻田大学人间科学学院,东京 163-8001 |
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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”（17ATQ007） |
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| 摘 要： | 智慧政府是电子政务的下一代更迭,受到各国的广泛关注。智慧政府可以通过各部门间的信息协同提升城市运行管理的效率。当前对智慧政府信息协同的研究主要集中于研究智慧政府信息协同的机制,少有对智慧政府信息协同网络结构现状进行识别与分析的研究。本文采用命名实体识别的方法基于目标数据源(智慧政府相关政策文件)中识别出的中国智慧政府信息协同网络的节点(政府部门)数据及节点关系(各个政府部门间的信息协同关系)数据,得到中国智慧政府信息协同网络结构,并对这些数据进行可视化处理。在此基础上采用社会网络分析中的度中心性方法,把各个节点按其对整个网络影响力的强弱排序;采用k-plex分析方法,识别出对整个网络具有较强影响力的节点。研究结果显示,中国智慧政府信息协同网络共包含34个节点和355组节点关系。在节点中,国务院节点对整个网络的影响力最强,中国气象局节点对整个网络的影响力最弱。在节点关系中,国家发展和改革委员会节点与国务院节点间的节点关系对整个网络具有较强的影响力,像这样具有较强影响力的节点关系共28组。本研究得到的结果可用来指导今后中国智慧政府信息协同网络优化与发展的侧重方向。
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| 关 键 词： | 智慧政府 信息协同 网络识别 网络分析 |
Awareness and Analysis of the Structure of the Information Synergy Network in Chinas Smart Government |
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| Hu Mo,Ma Jie,Zhang Yunkai,Wu Bo.Awareness and Analysis of the Structure of the Information Synergy Network in Chinas Smart Government[J].Journal of the China Society for Scientific andTechnical Information,2020,39(1):47-56. |
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| Authors: | Hu Mo Ma Jie Zhang Yunkai Wu Bo |
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| Institution: | (School of Management,Jilin University,Changchun 130022;Information Resources Research Center,Jilin University,Changchun 130022;School of Human Sciences,Waseda University,Tokyo 163-8001) |
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| Abstract: | Smart government is the next generation of e-government, which is an important issue for various countries.The efficiency of urban operation and management can be improved as a result of information synergy among various smart government departments. At present, research on intelligent government information synergy focuses mainly on its mechanism, and there are few studies regarding an awareness and analysis of the current structure of smart government information synergy networks. Based on relevant policy documents related to smart government as the target data sources,the method employed in this study was entity identification;the aim was to identify data of Chinas Smart Government Information Synergy Network and the synergistic relationship involving data of various government departments. Thus, the structure of this network can be acquired;subsequently, data can be visualized. On this basis, the degree centrality method(social network analysis) was adopted to rank each node according to its influence on the entire network. A k-plex analysis was used to identify the nodes that had a strong influence on the network. The results show that there are 34 nodes and 355 groups of nodes in Chinas Smart Government Information Synergy Network. Further, the State Council is the most influential node in the network, whereas the China Meteorological Administration is the least influential. The node relationship between the National Development and Reform Commission and the State Council has a strong influence on the entire network. In fact, there are 28 groups of node relationships with this type of strong influence. The results of this study can be used to guide the future direction of optimization and development of Chinas Smart Government Information Synergy Network. |
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| Keywords: | smart government information synergy network awareness network analysis |
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