Mental Disorder Detection and Measurement Using Latent Dirichlet Allocation and SentiWordNet

Due to the emergence of social platforms, people tend to posting their diaries and feeling online for sharing with others. In this paper, we aim to predict whether a user is getting depressed or not through his blog posts on the Internet. For this purpose, we use Latent Dirichlet Allocation (LDA) to find out top frequency words appearing in a user´s diaries and use SentiWordNet to calculate the emotion score of the user. Experimental results show that our method is useful in the diagnosis of mental disorder detection in social platforms.