基于多元媒体数据的教育舆情情绪可视化-《郑州大学学报(工学版)》

文章信息/Info

Title:: Visualization of Public Opinion Emotion in Education Based on Multiple Media Data

Author(s):: Liang Yitao; Wang Changbo; School of Computer Science and Software Engineering, East China Normal University, Shanghai, 200062

Keywords:: Visual analysis; public opinion in education Sentiment analysis; Network media data; Sentiment dissemination

摘要:: 教育舆情研究在危机公关、舆情引导等领域具有重要作用。目前，网络已经成为民众发表文章和评论的重要阵地。然而，如何识别网络教育舆情中的情绪倾向与情绪传播模式，并且在众多媒体平台中对比分析教育舆情情绪的特点，是当前舆情研究面临的一个挑战。针对该特点，我们设计实现了教育舆情情绪可视化系统。首先，根据与目标用户的讨论定义了教育舆情情绪分析的需求；其次，利用情绪识别算法识别文本情绪，并根据情绪传播模型提出了情绪传播算法；然后，设计了多个可交互式图，允许用户进行多媒体平台的对比分析。最后，基于2015年网络教育舆情数据进行案例分析，表明文中设计的可视化系统能够满足用户需求，并能支持舆情引导、危机公关中的媒体平台选择。

Abstract:: The research of public opinion on education had important values in the field of crisis management, public opinion guidance and so on. At present, Internet has become the main channel for people to express their opinions. However, distilling the emotion trend of public opinion and propagation mechanisms of the emotion, and analyzing the characteristics of emotion on multiple media platforms were still challenges. Therefore, a visualization system of emotion on education public opinion was designed. Firetly, the requirements of emotion analysis of public opinion were defined after the discussions with the users. Secondly, the emotion recognition algorithm was used to recognize emotion of text, and the emotion propagation algorithm was proposed based on the emotion propagation model. Thirdly, multiple interactive views were designed, which allows users to do comparative analysis on different online media platforms, and analyzed propagation mechanisms of emotion. Lastly, case studies on network data of education in 2015 showed that the system could meet the requirements of users and effectively support users’ selection of media platforms in public opinion guidance and crisis managment.