Shamsuddeen Hassan Muhammad, Idris Abdulmumin, A. Ayele, N. Ousidhoum, David Ifeoluwa Adelani, Seid Muhie Yimam, Meriem Beloucif, Saif M. Mohammad, Sebastian Ruder, Oumaima Hourrane, P. Brazdil, Felermino M. D. A. Ali, Davis David, Salomey Osei, Bello Shehu Bello, Falalu Ibrahim, T. Gwadabe, Samuel Rutunda, Tadesse Destaw Belay, Wendimu Baye Messelle, Hailu Beshada Balcha, S. Chala, Hagos Tesfahun Gebremichael, Bernard Opoku, Steven Arthur

Paper

Abstract

Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yoruba) from four language families (Afro-Asiatic, English Creole, Indo European, and Niger-Congo). We describe the data collection methodology, annotation process, and related challenges when cu-rating each of the datasets. We also build different sentiment classification baseline models on the datasets and discuss their usefulness.