Machine Learning-Based Approaches in the Detection of Suicide From Social Media Comments

Abstract

Suicidal tendencies have increased today due to nuclear organization of families and rapid urbanization around the world. Loneliness, aggression, and fast-moving daily lives make the youths and the aged persons depressed. Most of the time, they are involved in mutual relationships on social media. Social media posts and chats, thus, become an important resource from where we can find one's mental illness level and suicidal tendances. The most-used keywords are taken from an open database and are analyzed. ML algorithms like random forest, support vector classifier, and KNN are used to train and predict a person's suicide attempt. Out of these algorithms, SVC produces greater accuracy. To generate more accuracy, word sets shall be robust.