用AI分析37万用户梦境，发现疫情改变人们潜意识心理状态
Social Media Data Mining With Natural Language Processing on Public Dream Contents
- 用LLaMA 3.1-8B微调模型，精准识别梦境文本情感
- 疫情后梦境负面情绪占比显著上升，积极情绪下降
- 适合关注心理健康、社会心理学的研究者
新冠疫情深刻改变了全球生活方式，导致物理隔离加剧，并加速了工作、教育与社交活动的数字化转型。本研究通过分析Reddit r/Dreams社区中分享的梦境内容，考察疫情对心理健康的影响。该平台拥有超过374,000名订阅者，提供了丰富的数据源以探索疫情下潜意识反应。我们采用统计方法评估了疫情前后梦境中积极、消极与中性情绪的变化。为提升分析精度，使用标注数据对LLaMA 3.1-8B模型进行微调，实现对梦境内容的情感精确分类。研究结果揭示了梦境内容中的模式变化，为理解疫情对心理状态的影响及其对潜意识过程的作用提供了新视角。该研究凸显了疫情期间心理图景的深刻转变，以及梦境作为公共健康指标的重要性。
原文摘要 · Abstract (English)
The COVID-19 pandemic has significantly transformed global lifestyles, enforcing physical isolation and accelerating digital adoption for work, education, and social interaction. This study examines the pandemic's impact on mental health by analyzing dream content shared on the Reddit r/Dreams community. With over 374,000 subscribers, this platform offers a rich dataset for exploring subconscious responses to the pandemic. Using statistical methods, we assess shifts in dream positivity, negativity, and neutrality from the pre-pandemic to post-pandemic era. To enhance our analysis, we fine-tuned the LLaMA 3.1-8B model with labeled data, enabling precise sentiment classification of dream content. Our findings aim to uncover patterns in dream content, providing insights into the psychological effects of the pandemic and its influence on subconscious processes. This research highlights the profound changes in mental landscapes and the role of dreams as indicators of public well-being during unprecedented times.
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