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.
The ISSP is a cross-national collaboration program conducting annual surveys on diverse topics relevant to social sciences. Established in 1984, it includes members from various cultures around the globe. Over one million respondents have participated in ISSP surveys, and all collected data and documentation are available free of charge.
The WHO report on adolescent mental health describes actions undertaken by international development organizations to address adolescents’ mental health needs at the country level. It highlights the inadequacy of current efforts and the need for more coordinated and comprehensive interventions.
This dataset contains survey responses from individuals in the tech industry about their mental health, including questions about treatment, workplace resources, and attitudes towards discussing mental health in the workplace. By analyzing this dataset, we can better understand how prevalent mental health issues are among those who work in the tech sector—and what kinds of resources they rely upon to find help—so that more can be done to create a healthier working environment for all.