Arabic Sentiment Analysis

Congratulations to All Winners!






First: Wissam Antoun
Second: Abdullah Alharbi / Ali Salhi
Third: CS-UM6P (Team)




Challenge Details


Sentiment Analysis is to build machine learning models that can determine the tone (positive, negative, neutral) of the text (e.g., movie reviews, tweets).

It is one of most important and standard tasks in NLP.  However, Arabic sentiment analysis has not been studied at level as high as other languages, e.g., English, Chinese, French. One of the key factors is the lack of high-quality and large-scale training data. 

In our challenge, we will release 100K annotated tweets for Arabic sentiment analysis. This dataset will also be extremely useful for building Arabic language models, which are essential for supporting other Arabic NLP tasks, such as Question&Answering, Machine Translation, and text generation.


Competition Timeline



Competition Tools

ASAD: A Twitter-based Benchmark Arabic Sentiment Analysis Dataset

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Competition Dataset

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Challenge Prizes

First Place $10,000
Second Place $5,000
Third Place $2,000