Despite improvements in the detection and treatment of serious mental diseases, suicide has remained an unsolvable public health issue.
Additionally, there is mounting evidence that social media and the Internet can affect actions related to suicide. Social media data analysis using machine learning offers a viable method for identifying long-term contextual factors that increase a person's risk of having suicidal thoughts and actions.
I developed a very basic suicidal ideation classifier using Natural Language Processing, a branch of machine learning, to determine if a text is likely to include suicidal thoughts or not. In this various machine learning algorithms are used and their accuracy is compared to get the best results.
Dataset Link: https://www.kaggle.com/datasets/nikhileswarkomati/suicide-watch
App Link: https://suicidal-text-classification.streamlit.app/