一个塞索托新闻头条新闻数据集用于情绪分析
Refuoe Mokhosi1, Casper-Shikali Shivachi2, Matello Sethobane1
1Faculty of Engineering and Technology, Botho University, Maseru Mall, West Wing, Thetsane, Lesotho.
Data in brief
|April 9, 2024
概括
本研究介绍了塞索托语新闻 (SN) 数据集,这是塞索托语情感分析 (SA) 和基于方面的情感分析 (ABSA) 的宝贵资源. 这个注释数据集旨在为数以百万计的塞索托语说者推进NLP研究.
科学领域:
- 自然语言处理 (NLP) 是一种自然语言处理.
- 计算语言学 计算语言学
- 非洲语言技术
背景情况:
- 情感分析 (SA) 研究在高资源语言中是先进的,但由于数据稀缺,在像塞索托这样的低资源非洲语言中落后.
- 有限的注释数据集阻碍了为塞索托语说者开发特定语言的NLP服务.
研究的目的:
- 介绍塞索托新闻 (SN) 数据集,这是SA和ABSA任务的注释集.
- 促进塞索托语言的NLP研究和开发.
- 为了解塞索托的公众论和媒体情绪提供一个有价值的资源.
主要方法:
- 从塞索托的在线报纸收集了ABSA的4651个标题和SA的2401个标题.
- 标注SA和ABSA任务的新闻标题,使用莱索托语的塞索托语拼写.
- 使用斯皮尔曼相关性和科恩卡帕指数指标验证数据集质量.
主要成果:
- 塞索托新闻 (SN) 数据集已成功创建并对SA和ABSA进行注释.
- 评价了注释质量,表明了良好的注释者之间的协议.
- 该数据集被认为是塞索托NLP研究的黄金标准资源.
结论:
- SN数据集对低资源非洲语言的NLP研究做出了重大贡献.
- 这种资源将使塞索托语说者在情绪分析方面取得进展.
- 预计这一数据集的可用性将刺激塞索托NLP的进一步研究和应用.
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