聊天GPT在广东语情绪分析中的有效性:比较研究
Ziru Fu1, Yu Cheng Hsu1, Christian S Chan2,3
1The Hong Kong Jockey Club Centre for Suicide Research and Prevention, Faculty of Social Sciences, The University of Hong Kong, Hong Kong SAR, China (Hong Kong).
Journal of medical Internet research
|January 30, 2024
概括
聊天GPT模型,GPT-3.5和GPT-4,在广东语情绪分析中取得了高准确性,优于传统方法. 这表明它们在分析资源不足的语言和专业领域的潜力.
科学领域:
- 自然语言处理自然语言处理.
- 计算语言学 计算语言学
- 人工智能的人工智能
背景情况:
- 情感分析在广东语中存在独特的挑战,因为其语言的独特性.
- 像ChatGPT这样的高级语言模型为这些挑战提供了潜在的解决方案.
研究的目的:
- 评估GPT-3.5和GPT-4对广东语情绪分析的有效性.
- 将他们的表现与基于词典和机器学习的方法在现实世界的咨询环境中进行比较.
主要方法:
- 分析了来自131个语网络辅导会议的6169条信息.
- 使用GPT-3.5和GPT-4进行简单提示的信息的情感标签.
- 模型性能与基于词典和机器学习方法 (线性回归,SVM,LSTM) 的比较.
主要成果:
- 在情绪分类方面,GPT-4获得了95.3%的准确率,GPT-3.5获得了92.1%的准确率.
- 这两种模型的表现都明显优于基于词典的方法 (37.2%的准确率) 和机器学习模型 (66%-70.9%的准确率).
结论:
- 聊天GPT模型在广东语情绪分析方面表现出卓越的准确性.
- 这些发现强调了ChatGPT在现实应用中的实用性,例如监控咨询服务和分析专业领域.
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