Depression: Twitter Dataset + Feature Extraction
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.
Introduction détaillée
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.
PlusJeu de données
HeartLink - Empathetic Psychological Model
HeartLink is an empathetic psychological model that uses a large language model fine-tuned on a large empathetic Q&A dataset. It can perceive users' emotions and experiences during conversations and provide empathetic responses using rich psychological knowledge, aiming to understand, comfort, and support users. The responses include emoji expressions to bridge the gap with users, offering psychological support and help during consultations.
tartuNLP/Reddit Anhedonia Dataset - hf-mirror
tartuNLP/reddit-anhedonia by huggingface-mirror (hf-mirror)
Hugging Face Dataset - lsy641/PsyQA
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