A Study on Automatic Detection of Cyberbullying using Machine Learning

With time, use of the internet has become very common among people, and thus the rise of internet usage has given birth to a problem of cyberbullying. Cyberbullying can have a serious impact on the psychological health of the person who is the victim of it. Hence, detection of cyberbullying is required on the internet or social media. Much research has been done in the field of detection of cyberbullying. Machine learning can be the one of the approaches that is used for automatic cyberbullying detection. This paper has studied some of the papers related to cyberbullying. Moreover, some NLP techniques and different models used for cyberbullying detection tasks have been reviewed. The graph, which is based on the papers reviewed, shows that the tf-idf is mostly used either directly or with a combination of other techniques for feature extraction in cyberbullying detection using machine learning.