Papers › Mazajak: An Online Arabic Sentiment Analyser
Mazajak: An Online Arabic Sentiment Analyser
Ibrahim Abu Farha, Walid Magdy
Sentiment analysis (SA) is one of the most useful natural language processing applications. Literature is flooding with many papers and systems addressing this task, but most of the work is focused on English. In this paper, we present {``}Mazajak{''}, an online system for Arabic SA. The system is based on a deep learning model, which achieves state-of-the-art results on many Arabic dialect datasets including SemEval 2017 and ASTD. The availability of such system should assist various applications and research that rely on sentiment analysis as a tool.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Sentiment Analysis | ASTD | CNN-LSTM | Average Recall | 0.62 | #1 of 1 | Archive leaderboard | report |
| Sentiment Analysis | ArSAS | CNN-LSTM | Average Recall | 0.90 | #1 of 1 | Archive leaderboard | report |
| Sentiment Analysis | SemEval 2017 Task 4-A | CNN-LSTM | Average Recall | 0.61 | #3 of 3 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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