Litcius/Paper detail

Detecting Cyberbullying Across Multiple Social Media Platforms Using Deep Learning

Maheep Mahat

20212021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)31 citationsDOI

Abstract

In today 's time social media platforms have taken over our lives. The number of people using these platforms keeps on increasing day by day. With the increase of social media usage, the person who is using these platforms become more exposed to the negative effects of using social media. Among many negative effects, cyberbullying is one of the major negative effects of using social media. People online get bullied which affects their mental health in a negative manner. It is an incredibly difficult task to detect cyberbullying on social media platforms especially due to the slangs that people make up regularly but even so this paper suggests a working implementation of an application that detects cyberbullying across multiple social media platforms using the data provided by Twitter, Wikipedia and Formspring. This paper makes use of Deep Learning for the purpose of detecting cyberbullying.

Topics & Concepts

Social mediaComputer scienceTask (project management)Internet privacyMultimediaPsychologyWorld Wide WebEngineeringSystems engineeringHate Speech and Cyberbullying DetectionAdvanced Malware Detection TechniquesBullying, Victimization, and Aggression