A linguistic representation scheme for depression prediction - with a case study

Abstract

In this paper, we propose a representation scheme for modeling linguistic and paralinguistic features (emotion and speech act features) of depression patients, based on which a diagnostic model is constructed. The model can be used to assist the identification of depression and predict the degree of depression. A case study with the micro-blog data from a real depression patient and three non-patients, is carried out to illustrate the discriminative power of the linguistic and paralinguistic features. The results demonstrate the ability of the proposed representation scheme to not only distinguish the patient from non-patients but also distinguish different stages of the patient.