一个癌症在线健康社区的定量语言分析
Mengque Liu1, Xinyan Fan2, Shuangge Ma3
1School of Journalism and New Media, Xi'an Jiaotong University.
The annals of applied statistics
|August 29, 2025
概括
分析在线肺癌支持帖子显示患者情绪发生了重大变化,通常与COVID-19的变化相吻合. 这项研究通过先进的语言网络分析增强了对患者幸福感的理解.
科学领域:
- 计算语言学
- 社会网络分析
- 公共卫生信息学
背景情况:
- 在线卫生社区 (OHC) 为患者提供支持和讨论提供了有价值的平台.
- 对OHC的语言分析可以提供患者情绪和心理状态的见解.
- 目前用于分析OHC的方法存在局限性,特别是在单词共发生网络分析方面.
研究的目的:
- 分析LUNGevity基金会肺癌支持社区 (LCSC) 数据中的语言模式.
- 开发和应用一个先进的词汇共发生网络分析模型.
- 确定肺癌患者及其关联人员的情绪和精神状态的时间变化.
主要方法:
- 使用一个两部分隐藏空间模型进行词汇共发生网络分析,并结合网络权重.
- 开发了惩罚性融合方法来识别未知的变化点和估计时间变化的网络.
- 分析了2018年4月至2022年2月期间LCSC的21028个职位.
主要成果:
- 在语言数据中发现了多个显著的变化点.
- 这些变化点与肺癌患者及其关联人员的情绪/心理状态的变化相关.
- 检测到已识别的变化点与COVID-19相关重大事件之间的对齐.
结论:
- 这项研究成功地确定了在线肺癌社区患者情绪的时间变化.
- 先进的网络分析模型为分析OHC的动态变化提供了可靠的方法.
- 这些发现突显了COVID-19流行病等外部事件对患者福祉的影响.
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