基于VAR模型的视频弹幕情绪与用户转发行为研究
Research on Video Barrage Emotion and User Forwarding Behavior Based on VAR Model
[目的/意义]公共健康危机舆情事件可能会对受众产生持续性影响。[方法/过程]本文以bilibili视频社交平台为例，基于情绪传染理论建构VAR时间序列模型，以此对420个舆情视频中弹幕情绪与用户转发行为进行深入剖析。[结果/结论]实证结果显示，视频弹幕中不同情绪对用户转发行为的影响具有一定差异性，其中，愤怒、惊喜和厌恶情绪对用户转发行为的影响是正向的；恐惧情绪负向影响用户的转发行为；而高兴、平静和悲伤情绪对用户的转发行为的影响并不显著。结论为我国公共健康危机舆情管理工作提供了重要的决策支持与理论依据。?????
信息传播、知识传播科学、科学研究
舆情危机机器学习弹幕情绪VAR模型
何颖,金永生.基于VAR模型的视频弹幕情绪与用户转发行为研究[EB/OL].(2024-03-15)[2025-10-16].http://www.paper.edu.cn/releasepaper/content/202403-193.点此复制
[Purpose/Significance] Public health crisis public opinion events may have a sustained impact on the audience. [Method/Process] This article takes Bilibili video social platform as an example, constructs a VAR time series model based on emotional contagion theory, and conducts in-depth analysis of bullet comments and user forwarding behavior in 420 public opinion videos. [Results/Conclusion] Empirical results show that different emotions in video barrage have certain differences in the impact on user forwarding behavior, among which anger, surprise, and disgust have a positive impact on user forwarding behavior; Fear emotions have a negative impact on user forwarding behavior; The influence of happy, calm, and sad emotions on user forwarding behavior is not significant. The conclusion proResearch on video barrage emotion and user forwarding behavior basedResearch on video barrage emotion and user Research on video barrage emotion and user forwarding behavior based on VAR model on machine learning and VAR modelvides important decision support and theoretical basis for the management of public health crisis public opinion in China.
Public opinion crisisMachine learningBarrage emotionsVAR model
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