Analysis of depression in social media texts through the Patient Health Questionnaire-9 and natural language processing.

Objective: Although depression in modern people is emerging as a major social problem, it shows a low rate of use of mental health services. The purpose of this study was to classify sentences written by social media users based on the nine symptoms of depression in the Patient Health Questionnaire-9, using natural language processing to assess naturally users' depression based on their results.

Methods: First, train two sentence classifiers: the Y/N sentence classifier, which categorizes whether a user's sentence is related to depression, and the 0-9 sentence classifier, which further categorizes the user sentence based on the depression symptomology of the Patient Health Questionnaire-9.