Researchers have developed Masader Plus, a web interface for browsing the Masader catalog of Arabic NLP datasets. The interface allows for data exploration, filtration, and API access to examine datasets. User interactions with the website are intended to provide a way to improve the dataset catalog itself. Why it matters: This interface lowers the barrier to entry for researchers seeking Arabic NLP datasets, facilitating more research in the field.
Researchers created Masader, the largest public catalog for Arabic NLP datasets, containing 200 datasets annotated with 25 attributes. They developed a metadata annotation strategy applicable to other languages. The paper highlights issues within current Arabic NLP datasets and suggests recommendations. Why it matters: This curated dataset directory helps lower the barrier to entry for Arabic NLP research and development.
KAUST organized an Arabic Sentiment Analysis Challenge where participants developed ML models to classify tweets as positive, negative, or neutral. The competition used the ASAD dataset with 55K tweets for training, 20K for validation, and 20K for final evaluation. The full dataset of 100K labeled tweets has been released for public use.
Researchers introduce ASAD, a new large-scale, high-quality Arabic Sentiment Analysis Dataset based on 95K tweets with positive, negative, and neutral labels. The dataset is launched with a competition sponsored by KAUST offering a total of 17000 USD in prizes. Baseline models are implemented and results reported to provide a reference for competition participants.
KAUST alumnus Abhinay Ramaprasad (M.S. '12, Ph.D. '17) has been awarded the Marie Skłodowska-Curie Fellowship from the European Commission. He will research malaria at the Francis Crick Institute in the U.K., focusing on the mechanisms of malaria parasite egress from red blood cells. Ramaprasad credits his time at KAUST and his work in Professor Arnab Pain's laboratory for preparing him for this opportunity. Why it matters: This fellowship recognizes the high-quality research training at KAUST and supports important work in combating a disease prevalent in many regions, reflecting KAUST's impact on global health.