Hate Speech Detection and Classification in Amharic Text with Deep Learning

2024-08-07 · Samuel Minale Gashe, Seid Muhie Yimam, Yaregal Assabie

Hate speech is a growing problem on social media. It can seriously impact society, especially in countries like Ethiopia, where it can trigger conflicts among diverse ethnic and religious groups. While hate speech detection in resource rich languages are progressing, for low resource languages such as Amharic are lacking. To address this gap, we develop Amharic hate speech data and SBi-LSTM deep learning model that can detect and classify text into four categories of hate speech: racial, religious, gender, and non-hate speech. We have annotated 5k Amharic social media post and comment data into four categories. The data is annotated using a custom annotation tool by a total of 100 native Amharic speakers. The model achieves a 94.8 F1-score performance. Future improvements will include expanding the dataset and develop state-of-the art models. Keywords: Amharic hate speech detection, classification, Amharic dataset, Deep Learning, SBi-LSTM

📄 PDF Abstract BibTeX arXiv:2408.03849

Code (0)

등록된 구현이 없습니다.

Tasks

Deep LearningHate Speech Detection

Exploring Boundaries and Intensities in Offensive and Hate Speech: Unveiling the Complex Spectrum of Social Media Discourse

2024-04-18 · Abinew Ali Ayele, Esubalew Alemneh Jalew, Adem Chanie Ali, Seid Muhie Yimam 외

The prevalence of digital media and evolving sociopolitical dynamics have significantly amplified the dissemination of hateful content. Existing studies mainly focus on classifying texts into binary categories, often ove…

Binary Classification regression

A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection

2018-06-01 · WS 2018 6 · Aditya Bohra, Deepanshu Vijay, Vinay Singh, Syed Sarfaraz Akhtar 외

Hate speech detection in social media texts is an important Natural language Processing task, which has several crucial applications like sentiment analysis, investigating cyberbullying and examining socio-political cont…

General Classification Hate Speech Detection Sentiment Analysis

Hate Speech Detection in Limited Data Contexts using Synthetic Data Generation

2023-10-04 · Aman Khullar, Daniel Nkemelu, Cuong V. Nguyen, Michael L. Best

A growing body of work has focused on text classification methods for detecting the increasing amount of hate speech posted online. This progress has been limited to only a select number of highly-resourced languages cau…

Data Augmentation Hate Speech Detection Synthetic Data Generation text-classification+1

Hypothesis Engineering for Zero-Shot Hate Speech Detection

2022-10-03 · TRAC (COLING) 2022 10 · Janis Goldzycher, Gerold Schneider

Standard approaches to hate speech detection rely on sufficient available hate speech annotations. Extending previous work that repurposes natural language inference (NLI) models for zero-shot text classification, we pro…

Hate Speech Detection Natural Language Inference Text Classification Zero-Shot Text Classification

Bridging Modalities: Enhancing Cross-Modality Hate Speech Detection with Few-Shot In-Context Learning

2024-10-08 · Ming Shan Hee, Aditi Kumaresan, Roy Ka-Wei Lee

The widespread presence of hate speech on the internet, including formats such as text-based tweets and vision-language memes, poses a significant challenge to digital platform safety. Recent research has developed detec…

Few-Shot Learning Hate Speech Detection In-Context Learning Transfer Learning