多标签多类情绪和情绪数据集来自印度尼西亚移动应用程序审查
Riccosan1, Karen Etania Saputra1
1Computer Science Department, School of Computer Science, Bina Nusantara University Bandung Campus, Jakarta, Indonesia 11480.
Data in brief
|September 28, 2023
概括
这项研究引入了一个新的印度尼西亚数据集,用于移动应用程序评论,分类情绪和情绪. 本资源帮助印尼语的自然语言处理 (NLP) 任务,解决了多语言文本分析的差距.
科学领域:
- 自然语言处理 (NLP) 是一种自然语言处理.
- 数据科学数据科学数据科学
- 计算语言学 计算语言学
背景情况:
- 移动应用程序评论为用户提供了关于应用程序性能和美学方面的宝贵反.
- 用户评论包含丰富的文本数据,反映了情绪和情绪,适合创建数据集.
- 现有的印尼文本数据集用于多标签,多类情绪分析是有限的.
研究的目的:
- 从公共移动应用程序评论中创建一个新的多标签,多类印尼语数据集.
- 用情感 (积极,消极,中立) 和情感 (愤怒,恐惧,悲伤,快乐,爱,中立) 值对数据集进行注释.
- 支持和推进印尼语的情感分析和文本分类研究.
主要方法:
- 收集公开的移动应用程序审查.
- 数据预处理,包括清洁和处理.
- 评论的注释有3种情感类别和6种情感类别.
主要成果:
- 成功生成了印度尼西亚移动应用程序评价的综合数据集.
- 数据集被注释为多标签,多类情绪和情绪分析.
- 该数据集解决了印尼资源对于高级文本分类任务的稀缺问题.
结论:
- 开发的数据集是NLP研究的宝贵资源,特别是对印尼人的情感和情感分析.
- 这项工作通过为多标签文本分类提供急需的数据集,为该领域做出贡献.
- 该数据集有助于进一步研究了解用户在移动应用程序评论中表达的情绪和情绪.
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