通过社交媒体情绪分析,评估错误信息对围绕堕胎的公众情绪的影响
Brianna White1, Fekede Kumsa1, Nupur Singh1
1Center for Biomedical Informatics, Department of Pediatrics, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
Studies in health technology and informatics
|October 23, 2023
概括
研究人员正在使用自然语言处理 (NLP) 来分析社交媒体对妇女获得生殖健康服务,特别是堕胎的情绪. 本研究探讨了生殖错误信息与公共话语方向之间的联系.
科学领域:
- 计算社会科学 计算社会科学
- 公共卫生信息学 公共卫生信息学
- 自然语言处理自然语言处理.
背景情况:
- 社交媒体可以快速收集数据,以追踪公共卫生威胁.
- 分析在线话语对于了解关于敏感健康话题的公众情绪至关重要.
- 该团队之前的工作已经利用NLP对社交媒体数据的情绪分析.
研究的目的:
- 探索关于妇女生殖健康保健,特别是堕胎准入的社交媒体信息的情感分类.
- 调查与生殖有关的错误信息与公众情绪/话语之间的相关性.
- 评估精心调整的NLP模型对分析社会行为数据的有用性.
主要方法:
- 使用微调的自然语言处理 (NLP) 模型,特别是DistilRoBERTa.
- 收集和分析在社交网络上共享的社会行为数据.
- 应用情绪分类技术来识别公共话语的趋势.
主要成果:
- 该研究是一项正在进行中的工作,重点是方法论的开发.
- 最初的调查结果旨在确定错误信息和公众情绪之间的相关性.
- 这项研究展示了先进的NLP用于与健康相关的社交媒体分析的应用.
结论:
- 精心调整的NLP模型对分析公众对生殖健康保健的情绪显示出希望.
- 了解社交媒体话语可以帮助识别和打击生殖健康错误信息.
- 这种方法提供了一种可扩展的方法来监测公众对关键健康问题的意见.
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