Abstract
With the ever so growing internet, its influence over the society has deepened, and one such example is social media as even children are quite active on social media and can be easily influenced by it, social media can be a breeding ground for cyberbullying, which can lead to serious mental health consequences for victims. To counter such problems, content moderation systems can be an effective solution. They are designed to monitor and manage online content, with the goal of ensuring that it adheres to specific guidelines and standards. One such system based on natural language processing is described in the following paper, and various algorithms are compared to increase accuracy and precision. After testing the application, logistic regression yielded maximum precision and accuracy among the other algorithms.
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Gulati, G., Jha, H.A., Jain, R., Sharma, M., Chaudhary, V. (2024). Content Moderation System Using Machine Learning Techniques. In: Hassanien, A.E., Castillo, O., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. ICICC 2023. Lecture Notes in Networks and Systems, vol 731. Springer, Singapore. https://doi.org/10.1007/978-981-99-4071-4_58
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DOI: https://doi.org/10.1007/978-981-99-4071-4_58
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