Research Area:  Machine Learning
This research is based on the CLEF/eRisk 2017 pilot task which is focused on early risk detection of depression. The CLEF/eRsik 2017 dataset consists of text examples collected from messages of 887 Reddit users. The main idea of the task is to classify users into two groups: risk case of depression and non-risk case. This paper considers different feature sets for depression detection task among Reddit users by text messages processing. We examine our bag-of-words, embedding and bigram models using the CLEF/eRisk 2017 dataset and evaluate the applicability of stylometric and morphological features. We also perform a comparison of our results with the CLEF/eRisk 2017 task report.
Author(s) Name:  Maxim Stankevich ; Vadim Isakov ; Dmitry Devyatkin and Ivan Smirnov
Conferrence name:  Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM
Publisher name:  SCITEPRESS
Paper Link:   https://www.scitepress.org/PublicationsDetail.aspx?ID=574TGed/pTI=&t=1