학술논문

Towards Suicide Prevention: A Natural Language Processing and Machine Learning Approach Integrated with Chatbot
Document Type
Conference
Source
2024 International Conference on Automation and Computation (AUTOCOM) Automation and Computation (AUTOCOM), 2024 International Conference on. :181-186 Mar, 2024
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Signal Processing and Analysis
Privacy
Ethics
Machine learning algorithms
Social networking (online)
Computational modeling
Mental health
Machine learning
Suicide text
Deep learning models
Transformer algorithm
Suicide prevention
Chatbot
Language
Abstract
The paper presents a prediction model for identifying suicide intent in social media messages, especially on Twitter and Reddit. A huge dataset of postings, including symptoms of suicide ideation or behaviour, was analyzed using natural language processing (NLP) techniques, and characteristics were collected to build a machine learning (ML) model. The prediction algorithm was subsequently incorporated into a functioning mental health chatbot, which will give users at risk of suicide relevant resources and help. The initiative intends to improve mental health and suicide prevention efforts while also considering critical ethical factors, such as respecting user privacy and ensuring that the chatbot does not replace professional mental health treatment.