task_categories:text-classification language:amh am region:us
---
language: 
- amh
pretty_name: "Amharic Hate Speech Dataset"
tags:
- am
task_categories:
-  text-classification
---

 [GitHub](https://github.com/uhh-lt/AmharicHateSpeech)

# Introduction
The Amharic Hate Speech data is collected using the Twitter API spanning from October 1, 2020 - November 30, 2022, considering the socio-political dynamics of Ethiopia in Twitter space. We used [WEbAnno](http://ltdemos.informatik.uni-hamburg.de/codebookanno-cba/) tool for data annotation; each tweet is annotated by two native speakers and curated by one more experienced adjudicator to determine the gold labels. A total of 15.1k tweets consisting of three class labels namely: Hate, Offensive and Normal are presented. Read our papers for more details about the dataset (see below).

# Amharic Hate Speech Data Annotation: Lab-Controlled Annotation
The dataset is annotated by two annotators and a curator to determine the gold labels.  

For more details, You can read our paper entitled:
1. [Exploring Amharic Hate Speech data Collection and Classification Approaches](https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2023-ayele-et-al-hate-ranlp.pdf)


