This dataset contains 20,000 labelled English tweets of depressed and non-depressed users. The data is collected using the Twitter API and includes feature extraction techniques such as topic modelling and emoji sentiment analysis. It is designed for mental health classification at the tweet level.
The Depression: Twitter Dataset + Feature Extraction is a valuable resource for researchers and developers working on mental health classification. It includes 20,000 labelled English tweets, collected using the Twitter API. The dataset provides feature extraction techniques such as topic modelling and emoji sentiment analysis, making it suitable for various machine learning and data analysis projects. The data is essential for understanding and predicting mental health conditions from social media content.
The data is originally source from (Sun et al,2021). (Liu et al, 2023) processed the data to make it a dataset vis huggingface api with taining/validation/testing splitting
The Chinese Psychological QA DataSet is a collection of 102,845 community Q&A pairs related to psychological topics., providing a rich source of data for research and development in psychological counseling and AI applications. Each entry includes detailed question and answer information, making it a valuable resource for understanding user queries and generating appropriate responses.
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。