Detection of Cyberbullying on Social Media Using Machine Learning

Detection of Cyberbullying on Social Media Using Machine Learning
Author(s):
B.PRASANNA KUMAR, Ch Vishnu Vardhan Reddy, Ch Phanendra Reddy, Ch Venkatesh, G.Mahanvith
Keywords:
Cyberbullying, Hate speech, Personal attacks, Machine learning, Feature extraction, Twitter, Wikipedia
Abstract
Cyberbullying is a major problem encountered on the internet that affects teenagers and also adults. It has led to mishappenings like suicide and depression. Regulation of content on Social media platforms has become a growing need. The following study uses data from two different forms of cyberbullying, hate speech tweets from Twitter and comments based on personal attacks from Wikipedia forums to build a model based on the detection of Cyberbullying in text data using Natural Language Processing and Machine learning. Three methods for Feature extraction and four classifiers are studied to outline the best approach. For Tweet data, the model provides accuracies above 90% and for Wikipedia data, it gives accuracies above 80%.
Article Details
Unique Paper ID: 155140 Publication Volume & Issue: Volume 8, Issue 12 Page(s): 1566 - 1569
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