Analysis of the Ethiopic Twitter Dataset for Abusive Speech in Amharic
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Abstract (arXiv)
In this paper, we present an analysis of the first Ethiopic Twitter Dataset for the Amharic language targeted for recognizing abusive speech. The dataset has been collected since 2014 that is written in Fidel script. Since several languages can be written using the Fidel script, we have used the existing Amharic, Tigrinya and Ge'ez corpora to retain only the Amharic tweets. We have analyzed the tweets for abusive speech content with the following targets: Analyze the distribution and tendency of abusive speech content over time and compare the abusive speech content between a Twitter and general reference Amharic corpus.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Dec 2019.
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Citing papers per year: 2023: 1; 2024: 3.
4 papers.
- 2023AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languagescited by 68
- 2024EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluationcited by 8
- 2024Exploring Boundaries and Intensities in Offensive and Hate Speech: Unveiling the Complex Spectrum of Social Media Discoursecited by 4
- 2024Hate Speech Detection and Classification in Amharic Text with Deep Learningcited by 0
- 2024Hate Speech Detection and Classification in Amharic Text with Deep Learning7 Aug 2024
- 2024Exploring Boundaries and Intensities in Offensive and Hate Speech: Unveiling the Complex Spectrum of Social Media Discourse18 Apr 2024
- 2024EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation20 Mar 2024
- 2023AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages17 Feb 2023