Cyber Bullying Detection on Social Media Using Machine Learning Algorithms- A Review

Abstract

In our modern life, the young people (“digital natives”) have grown in an era dominated by
new technologies where communications are pushed to be in quite a real-time level, and pose
no limits in establishing relationships with other people or communities. The fast growing use
of social media sites among the children and teens have made them vulnerable to get exposed
by bullying. Cyberbullying is known to cause some serious health, emotional, psychological,
and social issues among social media users. Now a days it is significantly important to create
a way in identifying bullies in sites to avoid damages in social media sites. Comments and the
bulling posts containing abusive words effect psychology of teens and demoralize them.
Through machine learning, it can identify the language patterns used by bullies and their
victims, and develop rules too automatically to detect cyber bullying content. The aim of this
paper is to review the literatures on cyberbullying detection in social media sites using
machine learning algorithms. It also gives in-depth analysis of each algorithm based on
their accuracy.