  Computational research on mental health disorders from written texts covers
an interdisciplinary area between natural language processing and psychology. A
crucial aspect of this problem is prevention and early diagnosis, as suicide
resulted from depression being the second leading cause of death for young
adults. In this work, we focus on methods for detecting the early onset of
depression from social media texts, in particular from Reddit. To that end, we
explore the eRisk 2018 dataset and achieve good results with regard to the
state of the art by leveraging topic analysis and learned confidence scores to
guide the decision process.

Machine Learning;Computation and Language;Machine Learning