Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Languages:
Amharic
Size:
10K - 100K
Tags:
am
Seid Muhie Yimam
commited on
Commit
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5be4997
1
Parent(s):
02f30cc
RANLP datasets
Browse files- README.md +12 -0
- dev.csv +0 -0
- test.csv +0 -0
- train.csv +0 -0
- with_annotators_dev.csv +0 -0
- with_annotators_test.csv +0 -0
- with_annotators_train.csv +0 -0
README.md
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[![](../../logo.png)](https://github.com/uhh-lt/amharicmodels/)
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# Introduction
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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).
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# Amharic Hate Speech Data Annotation: Lab-Controlled Annotation
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The dataset is annotated by two annotators and a curator to determine the gold labels.
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For more details, You can read our paper entitled:
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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)
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test.csv
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train.csv
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with_annotators_dev.csv
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with_annotators_train.csv
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