Abstract
The online atmosphere is conducive for building connections with people all around the world, surpassing geographical boundaries. However, accepting participation from everyone is at the cost of compromising with abusive language or toxic comments. Limiting people from taking part in the discussions is not a viable option just because of misbehaving users. The proposed framework in this research harnesses the power of deep learning to enable toxic online comment recognition. These comments are further categorized using natural language processing tools.
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29 March 2022
Retraction Noe to: Chapter “Using Bidirectional LSTMs with Attention for Categorization of Toxic Comments” in: A. Khanna et al. (eds.), International Conference on Innovative Computing and Communications, Advances in Intelligent Systems and Computing 1387, https://doi.org/10.1007/978-981-16-2594-7_49
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Tobias, Z., Bose, S. (2022). RETRACTED CHAPTER: Using Bidirectional LSTMs with Attention for Categorization of Toxic Comments. In: Khanna, A., Gupta, D., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1387. Springer, Singapore. https://doi.org/10.1007/978-981-16-2594-7_49
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