Twitter Hate Speech Dataset for the Saudi Dialect

Published: 20 December 2023| Version 2 | DOI: 10.17632/c2jpnv9yk6.2
Contributor:
Ali Alhazmi

Description

The data was performed by employing standard Twitter API on Arabic tweets and code-mixing datasets. The Data was carried out for a duration of three months, specifically from April 2023 to June 2023. This was done via a combination of keyword, thread-based searches, and profile-based search approaches as. A total of 120 terms, including various versions, which were used to identify tweets containing code-mixing concerning regional hate speech. To conduct a thread-based search, we have incorporated hashtags that are related to contentious subjects that are deemed essential markers for hateful speech. Throughout the data-gathering phase, we kept an eye on Twitter trends and designated ten hashtags for information retrieval. Given that hateful tweets are usually less common than regular tweets, we expanded our dataset and improved the representation of the hate class by incorporating the most impactful terms from a lexicon of religious hate terms (Albadi et al., 2018). We gathered exclusively original Arabic tweets for all queries, excluding retweets and non-Arabic tweets. In all, we obtained 200,000 Twitter data, of which we sampled 23k tweets for annotation.

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Categories

Natural Language Processing, Applied Computer Science, Text Mining, Social Media Analytics

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