Citation

Huang Y. Proceedings of the International Conference on Public Management, Digital Economy and Internet Techn 2023; 1: 560-564.

Copyright

(Copyright © 2023)

DOI

10.5220/0011752000003607

PMID

unavailable

Abstract

Suicide is a global problem, and the number of people suffering from suicidal ideation is increasing globally. Therefore, suicide risk assessment is critical. With the development of the Internet in recent years, social media has become an essential source of information for studying psychological disorders such as depression and suicide. To this end, this paper designed a two-layer BiLSTM attention network model, using users' posts on social media as input to assess users' suicidal ideation levels. In order to improve the performance of the model, this paper sorted the posts according to the time stamp when preprocessing the dataset and also used the pre- training language model BERT, which can obtain a more reasonable word vector representation than the word embedding model. This paper assesses this model on the dataset provided by CLPsych2019. The dataset was taken from Reddit and divided users into four categories: no, low, moderate, and severe. The final experimental results show that the Accuracy of the model proposed in this paper can reach 62%, and the Macro_F1 value reaches 0.438. So, the model is a suitable assessment method.

Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology (ICPDI 2022), pages 560-564.
ISBN 978-989-758-620-0