Predicting Risk of Suicide Attempt Based on Survey Data
1Satvik Aggarwal, Tejasav, S. Saminathan
Suicide is a leading cause of death the world over. Its prevalence makes it essential to come up with efficient means of determining which people are suicidal. Techniques used in data science can be helpful in this regard. Past studies in the area have analyzed several data sources such as censuses, social media websites and blogs. This study employs online survey data consisting of several categorical factors pertaining to an individual’s personal details and personality traits. Correlations between these factors and suicidality are found. Furthermore, multiple classification algorithms are implemented and evaluated for the purpose of predicting the individual as suicidal or not, following which he/she can be counseled.
categorical variables, classification, depression, risk factors, suicidality