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.
Dataset Card for Psychology Therapy Dataset : This dataset card aims to provide information about a dataset focused on psychology therapy conversations. Language(s) (NLP): Turkish (tr)
The Lothian Diary Project consists of 125+ audio/video recordings collected from residents of Edinburgh and the Lothian counties in Scotland. Participants discuss their experiences during different stages of the Covid-19 pandemic. The recordings are accompanied by transcriptions and demographic information.
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.