UTILIZING AI TECHNOLOGY TO PREVENT SUICIDAL BEHAVIOR BY ANALYSING SENTIMENTS EXPRESSED ON SOCIAL MEDIA PLATFORMS.

This study introduces a technique for leveraging sentiment analysis to detect potential suicide risk among social media users. Our approach utilizes machine learning to scrutinize the textual content of social media posts and identify signicant markers of suicidal behavior. Our methodology comprises data collection, data preprocessing, data labeling, machine learning model training, and model testing. The effectiveness of our approach is assessed using precision, recall, and F1 score metrics. The outcome of our evaluation demonstrates that our method is adept at detecting individuals who may be at risk of suicide on social media, yielding an impressive F1 score of 0.85.