THROUGH THE ALGORITHMIC LOOKING GLASS: MENTAL HEALTH REFLECTIONS ON SOCIAL MEDIA

Abstract

There is a major issue facing the world: a large number of young people are killing themselves. Understanding this tendency's upward direction is another difficulty. Investigating the causes of suicidal thoughts in individuals of all ages and devising strategies to persuade them to choose life instead are crucial. Social media serves as an essential medium for individuals to express their ideas, manners, and emotional states in the present period. This has prompted the question of whether social media post analysis may be used to determine if people are happy or unhappy, especially to identify moods that would point to suicide ideation. This study uses artificial intelligence and machine learning techniques to examine people's social media postings in order to assess their mental health, with a focus on indicators that might point to a suicide risk. According to the research, those who seem sad on social media have a high prevalence of suicide ideation. This study looked at the possibilities of using an individual's online behaviour to determine the risk that they are considering suicide. This study shows how social media analysis may be used to find and help people who are suicidal, offering fresh perspectives on identifying and evaluating suicidal thoughts and marking a major breakthrough in suicide prevention initiatives.