Detection of Cyberbullying on Social Media Using Machine learning
- Resource Type
- Conference
- Authors
- Jain, Varun; Kumar, Vishant; Pal, Vivek; Vishwakarma, Dinesh Kumar
- Source
- 2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Computing Methodologies and Communication (ICCMC), 2021 5th International Conference on. :1091-1096 Apr, 2021
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Electronic publishing
Social networking (online)
Encyclopedias
Machine learning
Computer architecture
Feature extraction
Depression
Cyberbullying
Hate speech
Personal attacks
Twitter
Wikipedia
- Language
Cyberbullying is a major problem encountered on internet that affects teenagers and also adults. It has lead to mishappenings like suicide and depression. Regulation of content on Social media platorms has become a growing need. The following study uses data from two different forms of cyberbullying, hate speech tweets from Twittter and comments based on personal attacks from Wikipedia forums to build a model based on 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%.