Abstract
With the more usage of Internet and online social media, platforms creep with lot of cybercrimes. Texts in the online platforms and chat rooms are aggressive. In few instances, people target and humiliate them with the text. It affects victim mental health. Therefore, there is a need of detecting the abuse words in the text. In this paper, a study of machine learning methods is done to identify the aggressive behavior. Accuracy can be improved by incorporating additional features.
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https://github.com/dhavalpotdar/cyberbullying-detection/tree/master/data
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Pawar, V., Jose, D.V. (2023). Machine Learning Methods to Identify Aggressive Behavior in Social Media. In: Dutta, P., Chakrabarti, S., Bhattacharya, A., Dutta, S., Shahnaz, C. (eds) Emerging Technologies in Data Mining and Information Security. Lecture Notes in Networks and Systems, vol 490. Springer, Singapore. https://doi.org/10.1007/978-981-19-4052-1_50
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DOI: https://doi.org/10.1007/978-981-19-4052-1_50
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