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This paper provides a detailed description of a new Twitter-based benchmarkdataset for Arabic Sentiment Analysis (ASAD), which is launched in acompetition3, sponsored by KAUST for awarding 10000 USD, 5000 USD and 2000 USDto the first, second and third place winners, respectively. Compared to otherpublicly released Arabic datasets, ASAD is a large, high-quality annotateddataset(including 95K tweets), with three-class sentiment labels (positive,negative and neutral). We presents the details of the data collection processand annotation process. In addition, we implement several baseline models forthe competition task and report the results as a reference for the participantsto the competition.

ASAD: A Twitter-based Benchmark Arabic Sentiment Analysis Dataset