Machine learningDeep learning / NLP / CV
多语言情感分析
多语言情感分析（Multilingual Sentiment Analysis, MSA）应用深度学习——最常见的是微调过的多语言语言模型，如mBERT或XLM-RoBERTa——来对两种或更多语言的文本进行情感极性（积极、消极、中性）分类，从而实现跨语言的意见挖掘，而无需为每种语言单独构建模型。
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来源
- Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzman, F., Grave, E., Ott, M., Zettlemoyer, L., & Stoyanov, V. (2020). Unsupervised Cross-lingual Representation Learning at Scale. Proceedings of ACL 2020, 8440–8451. DOI: 10.18653/v1/2020.acl-main.747 ↗
- Barnes, J., Klinger, R., & Wubben, S. (2022). Structured Sentiment Analysis as Dependency Graph Parsing. Computational Linguistics, 48(3), 693–744. DOI: 10.18653/v1/2021.acl-long.263 ↗
如何引用本页
ScholarGate. (2026, June 3). Multilingual Sentiment Analysis (Cross-Lingual Opinion Mining). ScholarGate. https://scholargate.app/zh/deep-learning/multilingual-sentiment-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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- 基于RoBERTa的分类深度学习↔ compare
- 句子嵌入深度学习↔ compare