The advancement of social media plays an important role in increasing the population of youngsters on the web. And it has become the biggest medium of expressing one’s thoughts and emotions. Recent studies report that cyberbullying constitutes a growing problem among youngsters on the web. These kinds of attacks have a major influence on the current generation’s personal and social life because youngsters are ready to adopt online life instead of a real one, which leads them into an imaginary world. So, we are proposing a system for early detection of cyberbullying on the web and comparing different machine learning Algorithms to obtain the optimal result. We are comparing four different algorithms which can be effectively used for the detection of cyberbullying, with the implementation of the bag of words algorithm with different n-gram methods. Comparatively naïve Bayes algorithm has the highest accuracy of 79% with trigram implementation of the bag of words algorithm.
cyber bullying, machine learning, naïve Bayes algorithm, decision tree algorithm, logistic regression algorithm, support vector machine algorithm
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