Mazajak: An Online Arabic Sentiment Analyser

Sentiment analysis is one of the most useful natural language processing applications. There are many papers and systems addressing this task, but most of the work is focused on English. Therefore, we present “Mazajak”, an online system for Arabic sentiment analysis.

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 system provides three-way sentiment classification to one of the classes (Positive, Negative, Neutral).

Mazajak provides many features such as sentiment analysis for a sentence, a file, or you can submit a Twitter account and get an analysis of the user. Moreover, we provide Mazajak as a free online Arabic Sentiment Analysis API.

Mazajak was created by Ibrahim Abu Farha and Dr. Walid Magdy at the ILCC, part of the School of Informatics, the University of Edinburgh. This project was funded by The Alan Turing Institute, UK. The details about the system were published in WANLP-2019, please cite the following paper:

  • Mazajak: An Online Arabic Sentiment Analyser. Ibrahim Abu Farha and Walid Magdy. In Proceedings of the Fourth Arabic Natural Language Processing Workshop (WANLP). 2019.
    [ PDF | BibTex ]
Mazajak is offered for free use for research purposes. For commercial usage, please contact the authors.

Sentence Sentiment Analysis

Here, you can check the sentiment of a given sentence.
The most recent model will be used to classify your sentence into one of three classes (positive, negative, neutral).
To avoid confusion, if your text is a non-Arabic text then the result will be neutral.

Input Sentence:


For any issues or enquiries please contact Ibrahim Abu Farha (i.abufarha@ed.ac.uk).
Mazajak API is offered for free use for research purposes. For commercial usage, please contact the authors.


Mazajak API 1.0
Author: Dr Walid Magdy and Ibrahim Abu Farha, University of Edinburgh
Copyright © 2019 The University of Edinburgh

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