The Weibo User Depression Detection Dataset is a large-scale dataset for detecting depression in Weibo users. It includes user profiles, tweets, and labels indicating whether the user is depressed. The dataset is useful for researchers working on mental health and social media analysis.
The Weibo User Depression Detection Dataset provides a comprehensive set of user data, including nicknames, genders, profiles, birthdays, follower and following counts, and tweet content. Each user is labeled as depressed or normal, making it suitable for machine learning models to detect depression from social media data.
Lingxin (SoulChat) is a psychological health large model fine-tuned with millions of Chinese long-text instructions and multi-turn empathetic dialogue data in the field of psychological counseling.
The Substance Abuse and Mental Health Data Archive (SAMHDA) provides a comprehensive collection of data sets related to mental health and substance use. It includes ongoing studies, population surveys, treatment facility surveys, and client-level data, offering valuable insights for researchers and policymakers.
MentalManip数据集是由Wang等人(2024b)引入的,专门用于检测和分类心理操纵的对话数据集。该数据集包含4000个多轮虚构对话,来源于在线电影剧本,并进行了多层次的标注,包括操纵的存在、操纵技巧和目标脆弱性。数据集的创建旨在通过高质量的标注确保数据的一致性和准确性,从而支持心理操纵检测的研究。