高校学生网络舆情的动态监测路径与防控机制研究
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摘要
[目的/意义]高校学生网络舆情的动态监测与防控一直是高校网络安全所关注的焦点。在新媒体环境下,如何精准地预测高校学生网络舆情的发生和演化,掌握高校学生网络舆情发生的动态和规律以便对其进行有效地防控已成为高校思想政治教育的核心工作。[方法/过程]为此,采用信息获取、数据清洗和信息聚类等网络舆情分析技术对高校学生网络舆情监测流程、监测方法和监测内容等予以研究。[结果/结论]结果表明以舆情信息聚类结果为基础,利用人工研判和技术手段相结合的方法可以提升对高校学生网络舆情的动态监测效率,进而可以有效地对高校学生网络舆情实施防控。
[Purpose/Significance]The dynamic monitoring and prevention of students' network public opinion has always been the focus of network security in Colleges and universities.Under the new media environment,how to accurately predict the occurrence and evolution of College Students' network public opinion and grasp the dynamics of College Students' public opinion has become the core work of Ideological and political education in Colleges and universities.[Methods/Processes]Therefore,the content,method and process of network public opinion monitoring for college students were studied by using network public opinion analysis techniques such as information acquisition,data cleaning and information clustering.[Methods/Processes]The results showed that based on the clustering results,the combination of manual research and technical means improved the dynamic monitoring efficiency of College Students' network public opinion,and then effectively implemented the prevention and control of network public opinion.
[Purpose/Significance]The dynamic monitoring and prevention of students' network public opinion has always been the focus of network security in Colleges and universities.Under the new media environment,how to accurately predict the occurrence and evolution of College Students' network public opinion and grasp the dynamics of College Students' public opinion has become the core work of Ideological and political education in Colleges and universities.[Methods/Processes]Therefore,the content,method and process of network public opinion monitoring for college students were studied by using network public opinion analysis techniques such as information acquisition,data cleaning and information clustering.[Methods/Processes]The results showed that based on the clustering results,the combination of manual research and technical means improved the dynamic monitoring efficiency of College Students' network public opinion,and then effectively implemented the prevention and control of network public opinion.
引文
[1]中国互联网络信息中心.第43次《中国互联网络发展状况统计报告》[EB/OL].http://www.cnnic.net.cn/,2019-06-12.
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[14]Heinrich G.Parameter Estimation for Text Analysis[R].Technical Report,2008.
[15]中共中央文献研究室.习近平关于青少年和共青团工作论述摘编[M].北京:中央文献出版社,2017.
[16]习近平.习近平谈治国理政[M].北京:外文出版社,2014.
[2]王福.移动图书馆场景化信息接受适配研究[D].长春:吉林大学,2018.
[3]陈福集,翁丽娟.基于系统动力学的移动环境下高校网络舆情应对策略研究[J].现代情报,2018,38(4):118-123,176.
[4]张广鑫,于振元.校园政治舆论引导与营造路径探[J].辽宁师范大学学报,2005,(1):56-59.
[5]汤力峰,赵昕丽.网络舆情与高校思想政治工作的应对[J].黑龙江高教研究,2007,(4):64-65.
[6]黄蜺.新媒体环境下大学生网络舆情实证研究——基于西安地区部分高校的调查分析[J].社会科学家,2014,(3):44-49.
[7]刘金荣.基于动态演变路径的网络舆情研判体系构建[J].图书馆学研究,2013,(5):32-35,97.
[8]邓尚民,董亚倩.基于AHP的高校网络舆情安全评估指标体系构建研究[J].情报杂志,2012,31(8):31-36.
[9]舒予,张黎俐.基于小波分析与人工神经网络的网络舆情预测[J].情报科学,2016,34(4):40-42,47.
[10]于卫红.基于多Agent的高校网络舆情监测与分析系统[J].现代情报,2017,37(10):53-57.
[11]习近平.习近平谈治国理政[M].北京:外文出版社,2014.
[12]Su Leona Yi-Fan,Michael A Cacciatore,Xuan Liang,et al.Analyzing Public Sentiments Online:Combining Human-and Computer-based Content Analysis[J].Information,Communication & Society,2017,(5):406-427.
[13]Blei D M,Ng A Y,Jordan M I.Latent Dirichlet Allocation[J].Journal of Machine Learning Research,2003,(3):993-1022.
[14]Heinrich G.Parameter Estimation for Text Analysis[R].Technical Report,2008.
[15]中共中央文献研究室.习近平关于青少年和共青团工作论述摘编[M].北京:中央文献出版社,2017.
[16]习近平.习近平谈治国理政[M].北京:外文出版社,2014.