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Journal of Library and Information Science in Agriculture ›› 2020, Vol. 32 ›› Issue (2): 14-21.doi: 10.13998/j.cnki.issn1002-1248.2019.10.19-1138

• Public opinion monitoring and management • Previous Articles     Next Articles

Subject Clustering and Evolutionary Trend of Public Opinion Documents in China

ZHANG Tao1, SUN Ruiying2, LI Zhongjun3   

  1. 1. Information, network center, Heilongjiang University, Harbin 150080;
    2. College of Information Management, Heilongjiang University, Harbin 150080;
    3. School of Journalism, Communication, Heilongjiang University, Harbin 150080
  • Received:2019-12-26 Online:2020-02-05 Published:2020-02-25

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Abstract: [Purpose/Significance] With the rapid development of public opinion research, it has attracted scholars in various disciplines and produced fruitful results. Research on the topic clustering and evolution trends of public opinion literature in China can intuitively reveal current research situation and research frontiers in the field. [Method/Process] A total of 1,361 articles published from 1998 to 2019 in the CSSCI database were used as research samples. Citespace and Tableau software were used to analyze the subject clustering and evolution trends of China's public opinion research. [Results/Conclusions] Based on the prediction data and knowledge graph analysis, the development of China's research into public opinions is analyzed and summarized, and related suggestions are proposed to provide a reference for subsequent research in this field.

Key words: public opinion and sentiment, literature research, knowledge graph, bibliometrics

CLC Number: 

  • G25
[1] Chen,C.CiteSpace II: Detecting and visualizing emergingtrends and transient patterns in scientific literature[J]. Journal of the American Society for Information Science and Technology,2006,57(3):359.
[2] 蒋晓宇. 基于tableau可视化业务报表设计与实现[J].数字图书馆论坛,2017(2):224-225.
[3] 王国平. Tableau数据可视化[M].清华大学出版社..2017.
[4] 裴雷,李向举,谢添轩等.中国信息政策研究主题的历时演进特征(1986-2015)[J].数字图书馆论坛,2016,146(7):19-27.
[5] 孙瑞英,王旭.基于文献计量的国内物联网研究现状分析[J].现代情报,2016,36(1):153-159.
[6] 张涛,蔡庆平,马海群.一种基于政策文本计算的政策内容分析方法实证研究[J].信息资源管理学报,2019,9(1):66-76.
[7] 济南铁道报社编委会.典型示范热点疏导为企业改革攻坚提供舆情支持[J].新闻战线,1999(2):42-43.
[8] 郭乐天. 互联网虚假信息的控制与网络舆情的引导[J].新闻记者,2005(2):23-26.
[9] 李明,曹海军.中国网络舆情研究13年(2005-2017):理论、方法与实践[J].情报杂志,2019,5(38):116-122.
[10] 曾润喜. 网络舆情的管控工作机制研究[J].图书情报工作. 2009,53(8):79-82.
[11] 刘毅. 略论网络舆情的概念、特点、表达与传播[J].理论界,2007,(1):11-12.
[12] 张一文,齐佳音,马君等.网络舆情与非常规突发事件作用机制——基于系统动力学建模分析[J].情报杂志,2010,29(9):1-6.
[13] 张涛,马海群.一种基于LDA主题模型的政策文本聚类方法研究[J].数据分析与知识发现,2018,21(9):59-65.
[14] 左蒙,李昌祖.网络舆情研究综述:从理论研究到实践应用[J].情报杂志,2017,36(10):71-78,140.
[15] 赵蓉英,王旭.突发事件网络舆情关键节点识别及导控对策研究——以"大贤村遭洪灾事件"为例[J].现代情报,2018,38(1):19-24,30.
[16] 张宝生,祁晓婷.基于科学知识图谱的我国网络舆情研究可视化分析[J].情报探索,2017,5:111-120.
[17] 孔建华. 国内网络舆情治理研究综述[J].电子政务,2018,12(192):67-78.
[18] 许鑫. 网络公共事件政府回应的现状、问题与策略——基于2007-2014年102个案例的实证分析[J].情报杂志,2016,35(07):80-85,60.
[19] 徐鹏. 新时代高校舆情治理优化路径研究[J].中国高等教育,2019,Z1:78-80.
[20] Pervin N, Fang F, Datta A, et al.Fast, scalable, and context-sensitive detection of trending topics in microblog post streams[J].ACM Transactions on Management Information Systems (TMIS),2013,3(4):19.
[21] Saura J R, Palos-Sanchez P,Grilo A.Detecting Indicators for Startup Business Success: Sentiment Analysis Using Text Data Mining[J].Sustainability,2019,11(3):1-14.
[22] 陈福集,游丹丹.基于系统动力学的网络舆情事件传播研究[J].中国高等教育,2015(9):118-122.
[23] 许敏,姜润强.网络思政教育与高校舆情管理融合探究[J].中国报业,2019,6:88-89.
[24] 赵敏. 论网络舆论生态系统的现状与善治[J].大理学院学报,2014,9(13):38-41.
[25] 谢金林. 网络舆论生态系统内在机理及其治理研究:以网络政治舆论为分析视角[J].上海行政学院学报,2013,14(4):90-101.
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