Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Languages:
Amharic
Size:
10K - 100K
Tags:
am
| language: | |
| - amh | |
| pretty_name: "Amharic Hate Speech Dataset" | |
| tags: | |
| - am | |
| task_categories: | |
| - text-classification | |
| # 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) | |