A Two-Stage Classification Chatbot for Suicidal Ideation Detection
- DOI
- 10.2991/978-94-6463-094-7_31How to use a DOI?
- Keywords
- Chatbot; Suicidal ideation detection; Deep learning; Mental health
- Abstract
Suicide remains one of the leading causes of death globally and is a serious public health problem. Compounded by the lack of mental health professionals and lack of access to mental health services, it is difficult for people with mental health issues to seek treatment. The advancements in artificial intelligence have led to the development of mental health digital solution, such as chatbots. A chatbot is a software application that simulates human conversations with users through text or voice interactions. Chatbots have been receiving increasing attention lately for its roles in providing alternative support and helping in filling the gaps in mental health care. Although there are many chatbots that are widely used for mental health, they are not designed to detect suicide risk. In this paper, a two-stage classification chatbot is proposed for suicidal ideation detection.
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jin Xuan Chan AU - Sook-Ling Chua AU - Lee Kien Foo PY - 2022 DA - 2022/12/27 TI - A Two-Stage Classification Chatbot for Suicidal Ideation Detection BT - Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022) PB - Atlantis Press SP - 405 EP - 412 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-094-7_31 DO - 10.2991/978-94-6463-094-7_31 ID - Chan2022 ER -