Depression is the most serious mental illness that affects both the mental and physical health of the human body. Depression detection is designed to predict the depression level of the sufferer via information collected from social platforms. Social media information of the users is in the form of text that helps to understand the mindset of the users. It is important to analyze the text information sequentially to understand the user’s mental state.
   Contextual representation focuses on analyzing the user’s text with its neighborhood and genre information. Context vector representation extracts relevant sentence-level context information from a sequence of text with word embedding that helps make accurate inferences and predictions on depression. Context vector representation produces better detection for text sequence-based depression detection.