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This paper provides an overview of the Arabic Sentiment Analysis Challengeorganized by King Abdullah University of Science and Technology (KAUST). Thetask in this challenge is to develop machine learning models to classify agiven tweet into one of the three categories Positive, Negative, or Neutral.From our recently released ASAD dataset, we provide the competitors with 55Ktweets for training, and 20K tweets for validation, based on which theperformance of participating teams are ranked on a leaderboard,https://www.kaggle.com/c/arabic-sentiment-analysis-2021-kaust. The competitionreceived in total 1247 submissions from 74 teams (99 team members). The finalwinners are determined by another private set of 20K tweets that have the samedistribution as the training and validation set. In this paper, we present themain findings in the competition and summarize the methods and tools used bythe top ranked teams. The full dataset of 100K labeled tweets is also releasedfor public usage, athttps://www.kaggle.com/c/arabic-sentiment-analysis-2021-kaust/data.

Overview of the Arabic Sentiment Analysis 2021 Competition at KAUST