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Depression is a common mental disorder characterized by high incidence, high risk for disability and suicide, which brings great harm to individuals, families and society.Moreover, it is relatively difficult to diagnose, treat, monitor and manage for its subtle onset and long course as well as the sufferers' poor help-seeking behaviors.The recently emerged artificial intelligence technologies have become a new way for the management of depression and depression-related suicide.Based on the challenging situations, achievements that have been made in the diagnosis and management of depression, and monitoring and management of depression-related suicide using artificial intelligence technologies were discussed, which could be the reference for further studies about depression.

This study analyzes users' needs based on questions and the adequacy and quality of content in responses from participants in the ZHIHU Q&A online community (the largest Q&A platform in China). It aims to provide a basis for improving the management of online Q&A systems and enhancement of depression literacy for platform users. Python was used to crawl the question and response records found on depression in the ZHIHU, and the hot question records were classified by k-means clustering. The top 100 hot question records were then selected, and this research manually marked the answers with more than 40 likes for each question based on five dimensions of objectivity, integrity, professionalism, persuasiveness and practicality. The query content contained 685 hot questions. The results of cluster analysis showed that the questions about depression could be divided into four categories: basic knowledge, social life, self-management/prevention and education. In the annotated answers, the frequency of responses of higher quality of objectivity, persuasiveness and practicality was 89.81%, 65.64% and 73.24%, respectively, while the proportion of those regarding higher quality of professionalism and integrity was 33.21% and 16.79%. Users were found to have a high rate of demand for depression health information, but most of the responses on depression in the ZHIHU community were low-level and inadequate. Professionals and qualified volunteers should be encouraged to provide standardized answers to popular questions and contribute to a high-quality Q&A system. More rigorous management of the ZHIHU community should be designed to provide a high quality educational resource for platform users.