马德拉斯:以泰米尔语电影评论为基础的情绪分析数据集
M Arunmozhi1, R Sunitha1, D Rajalakshmi1
1Department of Computer Science, Pondicherry University, Kalapet, Puducherry, 605014, India.
Data in brief
|October 23, 2025
概括
研究人员创建了MADTRAS,这是一个用于基于方面的情感分析 (ABSA) 的泰米尔电影评论数据集. 这个资源解决了数据稀缺问题,并帮助使用多语言BERT等模型分析泰米尔电影情绪.
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
- 情绪分析 情绪分析
背景情况:
- 在线平台促进母语表达,电影讨论很普遍.
- 基于方面的情感分析 (ABSA) 对于理解这些讨论中的意见至关重要.
- 泰米尔电影评论给ABSA带来了独特的挑战,原因是数据稀缺和语言的聚合性.
研究的目的:
- 策划和验证一个新的注释数据集,用于基于泰米尔电影评论的面向情感分析 (ABSA).
- 为解决泰米尔语情绪分析有限可用的数据集的关键挑战.
- 为了促进对低资源语言的细粒度情绪分析的研究.
主要方法:
- 一个注释的泰米尔电影评论数据集的策划,名为MADTRAS.
- 通过严格的内容和注释评估来确保数据集质量.
- 使用多语言BERT (mBERT) 并将其性能与其他深度学习 (DL) 模型进行比较.
主要成果:
- 成功开发和验证了MADTRAS数据集,这是泰米尔ABSA的宝贵资源.
- 通过使用mBERT实现竞争性表现,证明了策划数据集的有效性.
- 为未来的泰米尔语ABSA研究提供了一个基准.
结论:
- 马德拉斯数据集有效地解决了ABSA的泰米尔电影评论数据的稀缺问题.
- 开发的数据集能够更准确地分析泰米尔电影评论的情感.
- 这项工作为泰米尔的先进自然语言处理 (NLP) 研究铺平了道路.
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