Detecting Racist Text in Bengali: An Ensemble Deep Learning Framework

S. S. Saruar, Nusrat, Sadia
1/30/2024
cs.CL

No confident code implementation found for this paper.

Abstract

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{saruar2024detecting,
  title  = {Detecting Racist Text in Bengali: An Ensemble Deep Learning Framework},
  author = {S. S. Saruar and Nusrat and Sadia},
  year   = {2024},
  eprint = {2401.16748},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.16748v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2401.16748.svg)](https://codeofpaper.com/paper/2401.16748)

Discussion