Arabic Hate Speech Dataset 2023

Published: 21 February 2024| Version 3 | DOI: 10.17632/mcnzzpgrdj.3
, Qasem Abu Al-Haija,


Description of Jordanian Hate Speech Corpus (JHSC): The folder consists of two CSV files: 1. annotated-hatetweets-4-classes_train.csv Which contains (302,766) labeled tweets 2. annotated-hatetweets-4-classes_test.csv Which contains (100,923) labeled tweets Each file contains three features: 1. Tweet id: Unique ID given for each tweet (removed before training) 2. Text: The tweet text in Arabic, cleaned and pre-processed. 3. Label: the dataset has 4 labels: a. Negative: No hate speech is included in the tweet. b. Neutral: General tweet (add, prayer, no sentiment is included) c. Positive: A hate speech exists, bullying, sarcasm, racism, ...etc. d. Very positive: A severe hate speech exists; includes phrases that can cause fights, or very bad influence on people and society.


Steps to reproduce

Please cite the following paper if you use our dataset: Ahmad A, Azzeh M, Alnagi E, Abu Al-Haija Q, Halabi D, Aref A and AbuHour Y (2024) Hate speech detection in the Arabic language: corpus design, construction, and evaluation. Front. Artif. Intell. 7:1345445. doi: 10.3389/frai.2024.1345445


Princess Sumaya University for Technology


Artificial Intelligence, Natural Language Processing, Machine Learning, Information Classification, Detection System, Deep Learning


Amman, Jordan

Ministry of Higher Education and Scientific Research