Multi-Modal Emotion Recognition for Online Education Using Emoji Prompts

被引：0
|
作者：
Qin, Xingguo [1 ]
Zhou, Ya [1 ]
Li, Jun [1 ,2 ]
机构：
[1] Guilin Univ Elect Technol, Sch Comp Sci & Informat Secur, Guilin 541004, Peoples R China
[2] Guangxi Key Lab Image & Graph Intelligent Proc, Guilin 541004, Peoples R China
来源：
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 12期
基金：
中国国家自然科学基金;
关键词：
emotion recognition; emoji prompt; online education; multi-modal;
D O I：
10.3390/app14125146
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
Online education review data have strong statistical and predictive power but lack efficient and accurate analysis methods. In this paper, we propose a multi-modal emotion analysis method to analyze the online education of college students based on educational data. Specifically, we design a multi-modal emotion analysis method that combines text and emoji data, using pre-training emotional prompt learning to enhance the sentiment polarity. We also analyze whether this fusion model reflects the true emotional polarity. The conducted experiments show that our multi-modal emotion analysis method achieves good performance on several datasets, and multi-modal emotional prompt methods can more accurately reflect emotional expressions in online education data.
引用
收藏
页数：13
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