基于大数据技术的高校网络舆情监测与分析

Big Data Analytics for Monitoring of Network Public Opinion of Colleges

高校网络舆情具有主体特殊性、内容多元性和传播快速性等特点,当负面舆情出现时,传统“救火”式思维模式已不能有效地解决网络舆情危机的爆发、蔓延和扩散。高校应综合利用大数据的分布式信息抓取与处理、非结构化数据存储等技术,通过舆情热词云分析、舆情演化分析和业务部门关注度分析等方式,快速完成网络舆情数据的多源采集、清理融合、分析挖掘等一系列任务,实现网络舆情的有效监管。“厦理工e起来”的舆情案例应用结果表明,基于大数据技术的高校网络舆情监测与分析,可实现对高校学生思想动态的实时追踪、预测和研判,防范和及时解决高校网络舆情危机的蔓延和扩散,促进高校文明和谐发展。

Network public opinion of colleges has the characteristics to have particular subjects, diversified contents and rapid communication, and the traditional fire-distinguishing thinking mode can no longer effectively solve the outbreak, spread or diffusion of the negative network public opinions. Colleges and universities should make good use of the big data technologies of distributed capture and unstructured data storage as well as word cloud analysis, evolution analysis and department attention analysis to perform multi-source collection, cleaning, integration, analysis and mining of the data for network public opinion of colleges as soon as possible so as to achieve the effective supervision of the public opinion. The case study of E-XMUT public opinion management shows that big data analytics for monitoring of network public opinion of colleges can implement the real-time monitoring, prediction and judgment of college students thinking and can therefore prevent and solve the spread and diffusion of the college public opinion crisis that helping promote the harmonious development of colleges and universities.