使用自然语言处理方法在双极性人群中建立高性欲Reddit Corpus:Reddit的传染病学研究
Daisy Harvey1, Paul Rayson2, Fiona Lobban1
1Spectrum Centre for Mental Health Research, Division of Health Research, Lancaster University, Lancaster, United Kingdom.
JMIR infodemiology
|March 7, 2025
概括
这项研究开发了一种方法来识别Reddit关于双相情感障碍中过度性欲的帖子. 调查结果显示,关于这个话题的在线讨论增加了,这突显了它作为症状的重要性.
科学领域:
- 计算语言学计算语言学
- 心理健康信息学心理健康信息学
- 数字化表型化是指数字化表型化.
背景情况:
- 双极性障碍在全球影响2%,通常与高性欲等冒险行为有关.
- 过度性欲被污名化,阻碍了对个人的公开讨论和支持.
- 了解双相情感障碍中的高性欲对于开发有效治疗方法至关重要.
研究的目的:
- 开发和评估用于识别双相情感障碍患者中高性欲的Reddit帖子的方法.
- 使用自然语言处理创建了Reddit Corpus (TABoRC) 中关于双极的谈话和双极Reddit Corpus (HiB-RC) 中的过度性行为.
- 提供方法论洞察力和初步发现,对双相情感障碍的过度性欲讨论.
主要方法:
- 利用计算语言工具箱创建群体并推断人口统计变量.
- 应用语言调查和单词计数来测量关键的心理领域.
- 采用BERTopic进行主题建模,以确定突出的语言集群,并讨论道德考虑.
主要成果:
- HiB-RC包含来自816个用户的2146个帖子,每年帖子和用户的数量显著增加 (分别为91.65%和86.97%).
- 与双相情感障碍中高性欲相关的发布活动比一般的Reddit使用量增加了更多.
- 与TABoRC相比,HiB-RC显示了更多的负面语调,更多的性讨论和更少的健康讨论;确定了9个关键主题.
结论:
- 过度性欲是一种重要的症状,在Reddit上被双相情感障碍患者讨论.
- 需要系统地承认过度性欲是双相情感障碍的症状.
- 这项研究验证了一种计算语言框架,用于分析双相情感障碍中过度性欲的体验.
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