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We investigate the value-add of topic modeling in text analysis for depression, and for neuroticism as a stronglyassociated personality measure. Using Pennebaker’s Linguistic Inquiry and Word Count (L...
Markov chain Monte Carlo (MCMC) approximates the posterior distribution of latent variable models bygenerating many samples and averaging over them. In practice, however, itis often more convenient to...
Topic models can yield insight into how depressed and non-depressed individuals use language differently. In this paper, we explore the use of supervised topic models in the analysis of linguistic sig...

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