基于LDA的国外电子政府研究主题演化及可视化分析
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摘要
为了从整体把握国外电子政府研究的发展动态及未来发展趋势,以Web of Science中关于电子政府的检索结果为实验对象(共37 540篇文档),采用LDA主题模型挖掘出每一年电子政府研究中的潜在主题,运用社会网络、主题河等方法对主题之间的相关关系、主题演化的生命周期进行可视化呈现。通过主题演化分析结果,提出将国外电子政府研究划分为信息技术应用、公共管理与公共服务、数据开放与增值服务3个阶段,详细介绍了每个阶段的研究特征。最后,分析了当前国外电子政府研究热点,展望了未来电子政府研究的发展趋势。
In order to make a better understanding of the development stage and discover the future development trend of foreign e-government research,this paper uses e-government as the experimental object(37540 document) in Web of Science,using LDA thematic model excavates the potential themes in the research of e-government every year,and uses the social network,theme river and other methods to visualize the relationship between the themes and the life cycle of the theme evolution.Through the evolution of the theme,this paper proposes that the evolution of e-government research theme is divided into three stages: information technology application stage,public administration and public services stage,data open and value-added services stage,and introduces the characteristics of each stage. Finally,it analyzes the hot topic of E-government research and looks forward to the future trend of e-government research.
In order to make a better understanding of the development stage and discover the future development trend of foreign e-government research,this paper uses e-government as the experimental object(37540 document) in Web of Science,using LDA thematic model excavates the potential themes in the research of e-government every year,and uses the social network,theme river and other methods to visualize the relationship between the themes and the life cycle of the theme evolution.Through the evolution of the theme,this paper proposes that the evolution of e-government research theme is divided into three stages: information technology application stage,public administration and public services stage,data open and value-added services stage,and introduces the characteristics of each stage. Finally,it analyzes the hot topic of E-government research and looks forward to the future trend of e-government research.
引文
[1]董伟,贾东琴.国外电子政务研究进展分析:基于共词分析方法的研究[J].图书情报工作,2011,55(21):125-129.
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[5]王炳立.基于共现与共被引网络的国际电子政务研究进展可视化分析[J].情报科学,2016,34(1):20-25.
[6]BOLIVAR M P R,MUNOZ L A,HERNANDEZ A M L.Scientometric study of the progress and development of e-government research during the period 2000—2012[J].Information Technology for Development,2016,22(1):36-74.
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[8]ZHENG Y,ZHANG Y J,LAROCHELLE H.A deep and autoregressive approach for topic modeling of multimodal data[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2016,38(6):1056-1069.
[9]LU H M,WEI C P,HSIAO F Y.Modeling healthcare data using multiple-channel latent dirichlet allocation[J].Journal of Biomedical Informatics,2016,60(2):210-223.
[10]SONG G,LI Y,CHEN X,et al.Influential node tracking on dynamic social network:an interchange greedy approach[J].IEEE Transactions on Knowledge and Data Engineering,2017,29(2):359-372.
[11]马红,蔡永明.共词网络LDA模型的中文文本主题分析:以交通法学文献(2000—2016)为例[J].现代图书情报技术,2016,32(12):17-26.
[12]WANG Y,WANG J,LIAO H,et al.An efficient semi-supervised representatives feature selection algorithm based on information theory[J].Pattern Recognition,2017,61(1):511-523.
[13]李永忠,蔡佳.基于LDA的国内电子政务研究主题演化及可视化分析[J].现代情报,2017,37(4):158-164.
[14]TEH Y W,JORDAN M I,BEAL M J,et al.Hierarchical dirichlet processes[J].Journal of the American Statistical Association,2006,101(476):1566-1581.
[15]曹娟,张勇东,李锦涛,等.一种基于密度的自适应最优LDA模型选择方法[J].计算机学报,2008,31(10):1780-1787.
[16]U.S.Copyright Office.The library of congress[EB/OL].[2017-06-01].http:∥id.loc.gov/search/?q=&q=cs%3A%2F2Fid.loc.gov%2Fauthor ities%2Fsubjects.
[17]NATIONAL INFORMATION STANDARS ORGANIZATION.Information retrieval:application service definition&protocol specification:ANSI/NISO Z39.50-2003(S2014)[S].Baltimore:American National Standards Institute,2017:1-238.
[2]张璇,苏楠,杨红岗,等.2000—2011年国际电子政务的知识图谱研究:基于Citespace和VOSviewer的计量分析[J].情报杂志,2012,31(12):51-57.
[3]PRZEYBILOVICZ E,CUNHA M A,COELHO T R.The development of studies on electronic government in brazil:a bibliometric and sociometric study[C]∥International Conference on Information Resources Management.Ho Chi Minh City:AIS Electronic Library,2014:2-14.
[4]辛刚.国内外电子政务可视化比较研究[D].合肥:安徽大学,2012.
[5]王炳立.基于共现与共被引网络的国际电子政务研究进展可视化分析[J].情报科学,2016,34(1):20-25.
[6]BOLIVAR M P R,MUNOZ L A,HERNANDEZ A M L.Scientometric study of the progress and development of e-government research during the period 2000—2012[J].Information Technology for Development,2016,22(1):36-74.
[7]BLEI D M,NG A Y,JORDAN M I.Latent dirichlet allocation[J].Journal of Machine Learning Research,2003,3(4-5):993-1022.
[8]ZHENG Y,ZHANG Y J,LAROCHELLE H.A deep and autoregressive approach for topic modeling of multimodal data[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2016,38(6):1056-1069.
[9]LU H M,WEI C P,HSIAO F Y.Modeling healthcare data using multiple-channel latent dirichlet allocation[J].Journal of Biomedical Informatics,2016,60(2):210-223.
[10]SONG G,LI Y,CHEN X,et al.Influential node tracking on dynamic social network:an interchange greedy approach[J].IEEE Transactions on Knowledge and Data Engineering,2017,29(2):359-372.
[11]马红,蔡永明.共词网络LDA模型的中文文本主题分析:以交通法学文献(2000—2016)为例[J].现代图书情报技术,2016,32(12):17-26.
[12]WANG Y,WANG J,LIAO H,et al.An efficient semi-supervised representatives feature selection algorithm based on information theory[J].Pattern Recognition,2017,61(1):511-523.
[13]李永忠,蔡佳.基于LDA的国内电子政务研究主题演化及可视化分析[J].现代情报,2017,37(4):158-164.
[14]TEH Y W,JORDAN M I,BEAL M J,et al.Hierarchical dirichlet processes[J].Journal of the American Statistical Association,2006,101(476):1566-1581.
[15]曹娟,张勇东,李锦涛,等.一种基于密度的自适应最优LDA模型选择方法[J].计算机学报,2008,31(10):1780-1787.
[16]U.S.Copyright Office.The library of congress[EB/OL].[2017-06-01].http:∥id.loc.gov/search/?q=&q=cs%3A%2F2Fid.loc.gov%2Fauthor ities%2Fsubjects.
[17]NATIONAL INFORMATION STANDARS ORGANIZATION.Information retrieval:application service definition&protocol specification:ANSI/NISO Z39.50-2003(S2014)[S].Baltimore:American National Standards Institute,2017:1-238.