面向基于情绪分析数据集的孟加拉语文本
Mahmudul Hasan1,2, Md Rashedul Ghani1, K M Azharul Hasan1
1Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh.
Data in brief
|December 6, 2024
概括
研究人员开发了BANGLA_ABSA,这是一个新的数据集,用于以孟加拉语为基础的情感分析 (ABSA). 这个资源解决了有限数据的挑战,以分析孟加拉人的情绪.
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
- 社交媒体分析 社交媒体分析
背景情况:
- 对孟加拉语社交媒体文本的情绪分析至关重要,但由于缺乏注释资源而受到阻碍.
- 基于方面的情绪分析 (ABSA) 需要详细的数据来识别对文本中的特定方面的情绪.
研究的目的:
- 为解决孟加拉语面向基于情绪分析 (ABSA) 的资源短缺问题.
- 在孟加拉语中为ABSA引入高质量,手动注释的数据集.
主要方法:
- 开发了一个名为BANGLA_ABSA.的新注释数据集.
- 在四个领域手动注释评论:餐厅,电影,手机和汽车.
- 数据集被组织成 {Id,Comment,Aspect Category,Sentiment Polarity} 的元组.
主要成果:
- 创建了四个特定领域的数据集:餐厅_ABSA (801条评论),电影_ABSA (800条评论),手机_ABSA (975条评论) 和汽车_ABSA (1149条评论).
- 所有注释的评论都是复杂的或复合的句子,提供丰富的语言数据.
- 数据集的结构是为了在机器学习和深度学习研究中有效使用.
结论:
- 孟加拉语_ABSA数据集是孟加拉语自然语言处理研究的重要贡献.
- 这个资源将促进对孟加拉文本的情绪分析和机器学习的进步.
- 允许对孟加拉语社交媒体内容进行更复杂的基于方面的情绪分析.
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