Adapting Deep Learning Methods for Mental Health Prediction on Social Media

03/17/2020
by   Ivan Sekulić, et al.
0

Mental health poses a significant challenge for an individual's well-being. Text analysis of rich resources, like social media, can contribute to deeper understanding of illnesses and provide means for their early detection. We tackle a challenge of detecting social media users' mental status through deep learning-based models, moving away from traditional approaches to the task. In a binary classification task on predicting if a user suffers from one of nine different disorders, a hierarchical attention network outperforms previously set benchmarks for four of the disorders. Furthermore, we explore the limitations of our model and analyze phrases relevant for classification by inspecting the model's word-level attention weights.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/19/2022

Exploring Hybrid and Ensemble Models for Multiclass Prediction of Mental Health Status on Social Media

In recent years, there has been a surge of interest in research on autom...
research
04/20/2022

Res-CNN-BiLSTM Network for overcoming Mental Health Disturbances caused due to Cyberbullying through Social Media

Mental Health Disturbance has many reasons and cyberbullying is one of t...
research
06/05/2023

A Simple and Flexible Modeling for Mental Disorder Detection by Learning from Clinical Questionnaires

Social media is one of the most highly sought resources for analyzing ch...
research
07/08/2023

Embedding Mental Health Discourse for Community Recommendation

Our paper investigates the use of discourse embedding techniques to deve...
research
04/19/2021

UVCE-IIITT@DravidianLangTech-EACL2021: Tamil Troll Meme Classification: You need to Pay more Attention

Tamil is a Dravidian language that is commonly used and spoken in the so...
research
09/15/2022

Hierarchical Attention Network for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings

Automatic depression detection on Twitter can help individuals privately...
research
06/28/2023

A Framework for Identifying Depression on Social Media: MentalRiskES@IberLEF 2023

This paper describes our participation in the MentalRiskES task at IberL...

Please sign up or login with your details

Forgot password? Click here to reset