CautionSuicide: A Deep Learning Based Approach for Detecting Suicidal Ideation in Real Time Chatbot Conversation
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Abstract (arXiv)
Suicide is recognized as one of the most serious concerns in the modern society. Suicide causes tragedy that affects countries, communities, and families. There are many factors that lead to suicidal ideations. Early detection of suicidal ideations can help to prevent suicide occurrence by providing the victim with the required professional support, especially when the victim does not recognize the danger of having suicidal ideations. As technology usage has increased, people share and express their ideations digitally via social media, chatbots, and other digital platforms. In this paper, we proposed a novel, simple deep learning-based model to detect suicidal ideations in digital content, mainly focusing on chatbots as the primary data source. In addition, we provide a framework that employs the proposed suicide detection integration with a chatbot-based support system.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 37 references that are in the map. First posted on arXiv 2 Jan 2024.
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7 of 37 references.
References · 7
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
- 2017On orthogonality and learning recurrent networks with long term dependenciescited by 82
- 2019Suicidal Ideation Detection: A Review of Machine Learning Methods and Applicationscited by 31
- 2018Deep Gated Recurrent and Convolutional Network Hybrid Model for Univariate Time Series Classificationcited by 26
- 2019Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layerscited by 9
- 2023Cyberbullying in Text Content Detection: An Analytical Reviewcited by 2
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