通过社交媒体语言变化追踪双相情感障碍的长期发展轨迹
Linguistic trajectories of bipolar disorder on social media
- 基于用户自述推断诊断时间，分析社交媒体语言长期演变
- 确诊后语言特征出现广泛变化，涵盖情绪、药物、住院等多维度
- 发现情绪波动具12个月周期，符合季节性情绪变化规律
语言使用为双相情感障碍（BD）等情绪障碍提供了重要洞察，但以往研究多为横断面且规模有限。本文利用社交媒体记录，首次大规模揭示了与BD相关的语言纵向变化。通过新方法从用户自述中推断诊断时间，比较了自认患有BD、抑郁或无精神健康问题的用户。BD诊断出现时，语言发生广泛转变，体现情绪障碍、共病精神疾病、物质滥用、住院史、躯体共病、人际困扰、异常思维内容及语言连贯性下降。诊断后数年内，情绪症状讨论呈现周期性波动，主周期为12个月，与季节性情绪变化一致。结果表明，社交媒体语言能有效捕捉BD相关的语言与行为变化，可作为传统精神科队列研究的有力补充。
原文摘要 · Abstract (English)
Language use offers valuable insight into affective disorders such as bipolar disorder (BD), yet past research has been cross-sectional and limited in scale. Here, we demonstrate that social media records can be leveraged to study longitudinal language change associated with BD on a large scale. Using a novel method to infer diagnosis timelines from user self-reports, we compared users self-identifying with BD, depression, or no mental health condition. The onset of BD diagnosis corresponded with widespread linguistic shifts reflecting mood disturbance, psychiatric comorbidity, substance abuse, hospitalization, medical comorbidities, interpersonal concerns, unusual thought content, and altered linguistic coherence. In the years following the diagnosis, discussions of mood symptoms were found to fluctuate periodically with a dominant 12-month cycle consistent with seasonal mood variation. These findings suggest that social media language captures linguistic and behavioral changes associated with BD and might serve as a valuable complement to traditional psychiatric cohort research.
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