Anxious Depression Prediction in Real-time Social Data
7 Pages Posted: 7 May 2019
Date Written: March 14, 2019
Mental well-being and social media have been closely related domains of study. In this research a novel model, AD prediction model, for anxious depression prediction in real-time tweets is proposed. This mixed anxiety-depressive disorder is a predominantly associated with erratic thought process, restlessness and sleeplessness. Based on the linguistic cues and user posting patterns, the feature set is defined using a 5-tuple vector.
Keywords: Depression, Anxiety, Social media, Machine learning
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