Skip to main content

Research Repository

Advanced Search

Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes

Schoene, Annika M; Turner, Alexander P; De Mel, Geeth; Dethlefs, Nina


Annika M Schoene

Alexander P Turner

Geeth De Mel


Recent statistics in suicide prevention show that people are increasingly posting their last words online and with the unprecedented availability of textual data from social media platforms researchers have the opportunity to analyse such data. Furthermore, psychological studies have shown that our state of mind can manifest itself in the linguistic features we use to communicate. In this paper, we investigate whether it is possible to automatically identify suicide notes from other types of social media blogs in two document-level classification tasks. The first task aims to identify suicide notes from depressed and blog posts in a balanced dataset, whilst the second experiment looks at how well suicide notes can be classified when there is a vast amount of neutral text data, which makes the task more applicable to real-world scenarios. Furthermore we perform a linguistic analysis using LIWC (Linguistic Inquiry and Word Count). We present a learning model for modelling long sequences in two experiment series. We achieve an f1-score of 88.26% over the baselines of 0.60 in experiment 1 and 96.1% over the baseline in experiment 2. Finally, we show through visualisations which features the learning model identifies, these include emotions such as love and personal pronouns.


Schoene, A. M., Turner, A. P., De Mel, G., & Dethlefs, N. (in press). Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes. IEEE Transactions on Affective Computing,

Journal Article Type Article
Acceptance Date Jan 23, 2021
Online Publication Date Feb 5, 2021
Deposit Date Feb 1, 2021
Publicly Available Date Feb 8, 2021
Journal IEEE Transactions on Affective Computing
Electronic ISSN 1949-3045
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Keywords Natural language processing; Recurrent neural networks; Text classification
Public URL
Publisher URL


Article (2.1 Mb)

Copyright Statement
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

You might also like

Downloadable Citations