eftekhar-hossain/MUTE-AACL22

[AACL'22] A Multimodal Dataset for Bengali Hateful Memes Detection

🤐MUTE: A First Open Source Bengali Hateful Memes Dataset

📢 Paper ALERT

MUTE: A Multimodal Dataset for Detecting Hateful Memes (AACL-SRW 2022)
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque

👉 [Paper] [Dataset]

Download the MUTE Dataset

import gdown
# Replace 'YOUR_FILE_ID' with the actual file ID from the Google Drive link.
gdown.download("https://drive.google.com/uc?export=download&id=1ozTFUM7q27g7uckhPWUiQFwhROCiEUAc", "file.zip", quiet=False)

After running the cell, the dataset will be downloaded as file.zip

Unzip the file.zip

import zipfile
zip_ref = zipfile.ZipFile("file.zip", 'r')
zip_ref.extractall()
zip_ref.close()

After unzipping the file, the MUTE dataset will be shown in the current directory. In the MUTE folder, you can see three Excel files and one meme folder.

🐧Related Papers

• Deciphering Hate: Identifying Hateful Memes and Their Targets (arxiv) [Paper] [Code]
• A Multimodal Framework to Detect Target Aware Aggression in Memes (EACL'24) [Paper] [Dataset]
• Align before Attend: Aligning Visual and Textual Features for Multimodal Hateful Content Detection (EACL-SRW'24) [Paper] [Code]
• MemoSen: A Multimodal Dataset for Sentiment Analysis of Memes (LREC'22) [Paper] [Code]

Citation

If you find our works useful for your research and applications, please cite using this BibTeX:

@inproceedings{hossain2022mute,
  title={Mute: A multimodal dataset for detecting hateful memes},
  author={Hossain, Eftekhar and Sharif, Omar and Hoque, Mohammed Moshiul},
  booktitle={Proceedings of the 2nd conference of the asia-pacific chapter of the association for computational linguistics and the 12th international joint conference on natural language processing: student research workshop},
  pages={32--39},
  year={2022}
}

@article{hossain2024deciphering,
  title={Deciphering Hate: Identifying Hateful Memes and Their Targets},
  author={Hossain, Eftekhar and Sharif, Omar and Hoque, Mohammed Moshiul and Preum, Sarah M},
  journal={arXiv preprint arXiv:2403.10829},
  year={2024}
}

@article{hossain2024align,
  title={Align before Attend: Aligning Visual and Textual Features for Multimodal Hateful Content Detection},
  author={Hossain, Eftekhar and Sharif, Omar and Hoque, Mohammed Moshiul and Preum, Sarah M},
  journal={arXiv preprint arXiv:2402.09738},
  year={2024}
}

@inproceedings{ahsan2024multimodal,
  title={A Multimodal Framework to Detect Target Aware Aggression in Memes},
  author={Ahsan, Shawly and Hossain, Eftekhar and Sharif, Omar and Das, Avishek and Hoque, Mohammed Moshiul and Dewan, M},
  booktitle={Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)},
  pages={2487--2500},
  year={2024}
}

@inproceedings{hossain2022memosen,
  title={Memosen: A multimodal dataset for sentiment analysis of memes},
  author={Hossain, Eftekhar and Sharif, Omar and Hoque, Mohammed Moshiul},
  booktitle={Proceedings of the Thirteenth Language Resources and Evaluation Conference},
  pages={1542--1554},
  year={2022}
}