Detecting Racist Text in Bengali: An Ensemble Deep Learning Framework
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Abstract (arXiv)
Racism is an alarming phenomenon in our country as well as all over the world. Every day we have come across some racist comments in our daily life and virtual life. Though we can eradicate this racism from virtual life (such as Social Media). In this paper, we have tried to detect those racist comments with NLP and deep learning techniques. We have built a novel dataset in the Bengali Language. Further, we annotated the dataset and conducted data label validation. After extensive utilization of deep learning methodologies, we have successfully achieved text detection with an impressive accuracy rate of 87.94% using the Ensemble approach. We have applied RNN and LSTM models using BERT Embeddings. However, the MCNN-LSTM model performed highest among all those models. Lastly, the Ensemble approach has been followed to combine all the model results to increase overall performance.
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References · 5
- 2021BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Banglacited by 123
- 2019A BERT-Based Transfer Learning Approach for Hate Speech Detection in Online Social Mediacited by 95
- 2022Multimodal Hate Speech Detection from Bengali Memes and Textscited by 15
- 2023Interpretable Multi Labeled Bengali Toxic Comments Classification using Deep Learningcited by 6
- 2023Bengali Fake Review Detection using Semi-supervised Generative Adversarial Networkscited by 2
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