Due to the rapid growth of user interaction on different social media platforms, publicly
available social media data has increased substantially. The sheer amount of data and level …

Natural language processing researchers have proven the ability of machine learning
approaches to detect depression-related cues from language; however, to date, these efforts …

Depression harms. However, due to a lack of mental health awareness and fear of stigma,
many patients do not actively seek diagnosis and treatment, leading to detrimental …

For numerous years, researchers have employed social media data to gain insights into
users' mental health. Nevertheless, the majority of investigations concentrate on …

Users of social platforms often perceive these sites as supportive spaces to post about their
mental health issues. Those conversations contain important traces about individuals' health …

This paper proposes a new depression detection system based on LLMs that is both
interpretable and interactive. It not only provides a diagnosis, but also diagnostic evidence …

Depression is a prevalent and debilitating mental health condition that requires accurate
and efficient detection for timely and effective treatment. In this study, we utilized the E-DAIC …

Sentiment and lexical analyses are widely used to detect depression or anxiety disorders. It
has been documented that there are significant differences in the language used by a …

Psychologists have used tests and carefully designed survey questions, such as Beck's
Depression Inventory (BDI), to identify the presence of depression and to assess its severity …

Language provides a unique window into thoughts, enabling direct assessment of mental-
state alterations. Due to their increasing popularity, online social media platforms have …