Abstract

Antisocial behavior (ASB) is one of the ten personality disorders included in ‘The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and falls in the same cluster as Borderline Personality Disorder, Histrionic Personality Disorder, and Narcissistic Personality Disorder. It is a prevalent pattern of disregard for and violation of the rights of others. Online antisocial behavior is a social problem and a public health threat. An act of ASB might be fun for a perpetrator; however, it can drive a victim into depression, self-confinement, low self-esteem, anxiety, anger, and suicidal ideation. Online platforms such as Twitter and Reddit can sometimes become breeding grounds for such behavior by allowing people suffering from ASB disorder to manifest their behavior online freely. In this paper, we propose a proactive approach based on natural language processing and deep learning that can enable online platforms to actively look for the signs of antisocial behavior and intervene before it gets out of control. By actively searching for such behavior, social media sites can prevent dire situations leading to someone committing suicide.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.