  This paper provides a detailed description of a new Twitter-based benchmark
dataset for Arabic Sentiment Analysis (ASAD), which is launched in a
competition3, sponsored by KAUST for awarding 10000 USD, 5000 USD and 2000 USD
to the first, second and third place winners, respectively. Compared to other
publicly released Arabic datasets, ASAD is a large, high-quality annotated
dataset(including 95K tweets), with three-class sentiment labels (positive,
negative and neutral). We presents the details of the data collection process
and annotation process. In addition, we implement several baseline models for
the competition task and report the results as a reference for the participants
to the competition.
