Abstract:

Existing sentiment analysis focus on the emotional tendency, which are lack of detailed description of all kinds of emotions, they can’t intuitively reflect the emotional change of social groups. An emotional analysis method based on the combination of dependency parsing and artificial tagging was proposed. Facial expression animation to present emotions analysis was realized. The microblog crowd’s emotion in different areas for different social events was visualized. The experimental results show that the model could closely and effectively simulate the crowd emotion, and it could provide a new way of the analysis of network public opinion based on large data.

Key words: text analysis, microblog, sentiment analysis, visual computing

摘要：

针对已有的情感分析研究多侧重在情感的倾向性方面, 缺乏对各类情感的详细描述, 不能形象直观地反映社会群体的情感变化的问题, 提出一种基于依存句法和人工标注相结合的情感分析方法。该方法采用三维立体的人脸表情进行情感分析, 形象地呈现社会群体的情感变化。对于不同的社会事件, 以可视化方式来展现不同地区微博群体的情感。实验结果表明, 该模型可以有效地描述人群情感, 研究结果为基于大数据的网络舆情分析提供了一种新思路。

关键词: 文本分析, 微博, 情感分析, 可视计算