关于女权主义的社交媒体话语:一种用于Bangla语评论情绪分析的数据集
Md Mijanur Rahman1, Md Sumon Hosen1, Zaid Bin Sajid1
1Department of Computer Science and Engineering, Southeast University, 251/A Tejgaon I/A, Dhaka 1208, Bangladesh.
Data in brief
|February 2, 2026
概括
这项研究收集了来自社交媒体的6,830条孟加拉语关于女权主义的评论,以分析公众论和在线基于性别的暴力. 该数据集支持机器学习任务,如情绪和滥用语言分析.
科学领域:
- 计算社会科学 计算社会科学
- 自然语言处理自然语言处理.
- 性别研究是性别研究.
背景情况:
- 社交媒体平台在塑造孟加拉国关于妇女权利和女权主义的公共话语方面越来越有影响力.
- 了解公众对女权主义的看法在孟加拉国这样的社会文化多样化的环境中至关重要.
- 现有的研究缺乏全面的数据集来分析孟加拉语在线女权主义话语.
研究的目的:
- 创建一个高质量的,注释数据集6830孟加拉语评论女权主义从社交媒体.
- 为了促进在孟加拉语语文背景下对公众论,情绪和在线基于性别的暴力行为的分析.
- 支持与女权主义话语相关的机器学习和自然语言处理 (NLP) 任务.
主要方法:
- 从公开的Facebook,Instagram和Twitter群组和标签搜索 (例如#womensrights) 中系统地提取数据.
- 孟加拉语母语者手动注释以确保时事性和识别滥用语言.
- 将评论分为三个情绪类别:中立,负面和积极.
主要成果:
- 编制并注释了6,830个孟加拉语关于女权主义的评论的大量数据集.
- 该数据集适用于分析在线基于性别的暴力,情绪和滥用语言.
- 这些数据可以对孟加拉国社交媒体上的女权主义话语进行彻底审查.
结论:
- 精心策划的数据集为孟加拉国在线女权主义话语的NLP和机器学习研究提供了宝贵的资源.
- 这项工作有助于理解基于性别的在线互动和公众对孟加拉语女权主义的情绪.
- 这些发现支持进一步的监督学习应用程序来分析与性别问题相关的社交媒体内容.
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