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 …

Depression is a mental illness that negatively affects a person's well-being and can, if left
untreated, lead to serious consequences such as suicide. Therefore, it is important to …

In this paper we present our approach for detecting signs of depression from social media
text. Our model relies on word unigrams, part-of-speech tags, readabilitiy measures and the …

Depression is a common and serious mental illness that early detection can improve the
patient's symptoms and make depression easier to treat. This paper mainly introduces the …

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 …

Social media has become a vital platform for personal communication. Its widespread use
as a primary means of public communication offers an exciting opportunity for early …

This paper presents our winning solution for the Shared Task on Detecting Signs of
Depression from Social Media Text at LT-EDI-ACL2022. The task was to create a system …

Depression is a common illness involving sadness and lack of interest in all day-to-day
activities. It is important to detect depression at an early stage as it is treated at an early …

This paper presents a state-of-the-art solution to the LT-EDI-ACL 2022 Task 4: Detecting
Signs of Depression from Social Media Text. The goal of this task is to detect the severity …

This paper presents a set of classification experiments for identifying depression in posts
gathered from social media platforms. In addition to the data gathered previously by other …