Sentiment Analysis of Arabic Tweets: Feature Engineering and A Hybrid Approach (2018 · 30 citations)
This work addresses sentiment classification of Arabic tweets. Social media Arabic is noisy, informal and heavily dialectal, and most Arabic NLP tools target MSA, so they handle it poorly. The authors therefore restrict themselves to one variant, the Saudi Dialect, and build a hybrid system on a large corpus of Saudi…
Assessing the Linguistic Knowledge in Arabic Pre-trained Language Models Using Minimal Pairs (2022 · 5 citations)
The authors test how well Arabic pretrained BERT-based language models have actually learned Arabic grammar.
Cross-Linguistic Analysis of Eye Movement Patterns: Insights from the First Arabic Eye-Tracking Corpus for NLP (2026)
Most eye-tracking corpora used in NLP cover left-to-right Latin-script languages. Little is known about gaze behaviour in a cursive, right-to-left, morphologically rich language like Arabic. The authors use AraEyebility, which they describe as the first Arabic eye-tracking corpus built for NLP, to address this. In…

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Updated 1 November 2026