Detecting Hate Speech in Amharic Using Multimodal Analysis of Social Media Memes

Melese Ayichlie Jigar, Abinew Ali Ayele, Seid Muhie Yimam, Chris Biemann


Abstract
In contemporary society, the proliferation of hate speech is increasingly prevalent across various social media platforms, with a notable trend of incorporating memes to amplify its visual impact and reach. The conventional text-based detection approaches frequently fail to address the complexities introduced by memes, thereby aggravating the challenges, particularly in low-resource languages such as Amharic. We develop Amharic meme hate speech detection models using 2,000 memes collected from Facebook, Twitter, and Telegram over four months. We employ native Amharic speakers to annotate each meme using a web-based tool, yielding a Fleiss’ kappa score of 0.50. We utilize different feature extraction techniques, namely VGG16 for images and word2Vec for textual content, and build unimodal and multimodal models such as LSTM, BiLSTM, and CNN. The BiLSTM model shows the best performance, achieving 63% accuracy for text and 75% for multimodal features. In image-only experiments, the CNN model achieves 69% in accuracy. Multimodal models demonstrate superior performance in detecting Amharic hate speech in memes, showcasing their potential to address the unique challenges posed by meme-based hate speech on social media.
Anthology ID:
2024.trac-1.10
Volume:
Proceedings of the Fourth Workshop on Threat, Aggression & Cyberbullying @ LREC-COLING-2024
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Ritesh Kumar, Atul Kr. Ojha, Shervin Malmasi, Bharathi Raja Chakravarthi, Bornini Lahiri, Siddharth Singh, Shyam Ratan
Venues:
TRAC | WS
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
85–95
Language:
URL:
https://aclanthology.org/2024.trac-1.10
DOI:
Bibkey:
Cite (ACL):
Melese Ayichlie Jigar, Abinew Ali Ayele, Seid Muhie Yimam, and Chris Biemann. 2024. Detecting Hate Speech in Amharic Using Multimodal Analysis of Social Media Memes. In Proceedings of the Fourth Workshop on Threat, Aggression & Cyberbullying @ LREC-COLING-2024, pages 85–95, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Detecting Hate Speech in Amharic Using Multimodal Analysis of Social Media Memes (Jigar et al., TRAC-WS 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.trac-1.10.pdf