MindSET：通过大规模社交媒体数据推动心理健康基准测试
MindSET: Advancing Mental Health Benchmarking through Large-Scale Social Media Data
AI总结：
MindSET通过大规模社交媒体数据提升心理健康基准测试，提供超过1300万条注释帖子，显著提升诊断检测性能。
摘要：
社交媒体数据已成为研究心理健康的重要资源，提供了传统方法常遗漏的实时思想、情绪和行为洞察。在这一领域的发展受到心理健康分析基准数据集的推动；然而，大多数现有基准测试因数据有限、清理不足以及社交媒体内容本质上多样（例如多语言和有害内容）而过时。我们提出了一个新的基准数据集，MindSET，从Reddit中收集自报诊断信息，以解决这些限制。注释数据集包含超过1300万条注释帖子，涵盖七种心理健康状况，比以往的基准测试大超过一倍。为了确保数据质量，我们应用了严格的预处理步骤，包括语言过滤，并移除了不安全工作（NSFW）和重复内容。我们进一步使用LIWC进行了语言分析，以检查数据集中八个群体的心理学术语频率。为了展示数据集的用途，我们进行了二分类实验，使用微调的语言模型和词袋（BoW）特征进行诊断检测。在MindSET上训练的模型在诊断检测任务中持续优于在先前基准测试上训练的模型，实现了自闭症检测的F1分数最高达18点的提升。总体而言，MindSET为研究社交媒体与心理健康交汇点的学者提供了坚实的基石，支持早期风险检测和对新兴心理趋势的深入分析。
英文摘要：
Social media data has become a vital resource for studying mental health, offering real-time insights into thoughts, emotions, and behaviors that traditional methods often miss. Progress in this area has been facilitated by benchmark datasets for mental health analysis; however, most existing benchmarks have become outdated due to limited data availability, inadequate cleaning, and the inherently diverse nature of social media content (e.g., multilingual and harmful material). We present a new benchmark dataset, \textbf{MindSET}, curated from Reddit using self-reported diagnoses to address these limitations. The annotated dataset contains over \textbf{13M} annotated posts across seven mental health conditions, more than twice the size of previous benchmarks. To ensure data quality, we applied rigorous preprocessing steps, including language filtering, and removal of Not Safe for Work (NSFW) and duplicate content. We further performed a linguistic analysis using LIWC to examine psychological term frequencies across the eight groups represented in the dataset. To demonstrate the dataset utility, we conducted binary classification experiments for diagnosis detection using both fine-tuned language models and Bag-of-Words (BoW) features. Models trained on MindSET consistently outperformed those trained on previous benchmarks, achieving up to an \textbf{18-point} improvement in F1 for Autism detection. Overall, MindSET provides a robust foundation for researchers exploring the intersection of social media and mental health, supporting both early risk detection and deeper analysis of emerging psychological trends.
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