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Depression is one of the most common and a major concern for society. Propermonitoring using devices that can aid in its detection could be helpful toprevent it all together. The Distress Analysis Interview Corpus (DAIC) is usedto build a metric-based depression detection. We have designed a metric todescribe the level of depression using negative sentences and classify theparticipant accordingly. The score generated from the algorithm is thenlevelled up to denote the intensity of depression. The results show thatmeasuring depression is very complex to using text alone as other factors arenot taken into consideration. Further, In the paper, the limitations ofmeasuring depression using text are described, and future suggestions are made.

Detecting Levels of Depression in Text Based on Metrics