CHQ-SocioEmo:在消费者健康问题中识别社会和情感支持需求
Ashwag Alasmari1, Luke Kudryashov2, Shweta Yadav3
1King Khalid University, Abha, Saudi Arabia. ashwag.m.alasmari@gmail.com.
Scientific data
|May 27, 2023
概括
消费者寻求在线健康信息超出了基本事实,需要社会和情感支持. 一个新的数据集,CHQ-SocioEmo,通过对非信息需求的消费者健康问题进行注释来解决这个差距.
科学领域:
- 医疗信息学 医疗信息学
- 自然语言处理自然语言处理.
- 社交计算社会计算
背景情况:
- 公众越来越多地在网上寻找健康信息,往往需要的不仅仅是事实上的答案.
- 现有的研究和数据集专注于消费者健康问题的信息需求,忽视了社会和情感支持.
- 消费者健康问题的自动化系统必须识别和解决非信息需求.
研究的目的:
- 推出CHQ-SocioEmo,这是第一个公开可用的注释数据集,用于消费者健康问题的非信息需求.
- 为在线健康查询中理解和分类社会和情感支持需求提供资源.
- 用最先进的分类模型对数据集的实用性进行比较.
主要方法:
- 收集来自社区问答论坛的消费者健康问题.
- 标注收集到的问题与基本的情绪和社会支持需求.
- 开发并对CHQ-SocioEmo数据集与各种分类模型进行比较.
主要成果:
- CHQ-SocioEmo数据集是首个针对消费者健康方面的非信息需求的资源.
- 基准测试证明了数据集在培训和评估社会和情感支持需求分类模型中的有效性.
- 该数据集促进了消费者健康问题的自动回答系统的进步.
结论:
- 解决社会和情感支持对于在线健康信息搜索的满意性至关重要.
- CHQ-SocioEmo数据集为开发更全面的消费者健康问答系统提供了宝贵的资源.
- 未来的研究可以利用这个数据集来提高AI提供对健康问题的同情和支持性反应的能力.
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