Arabic has a wide range of varieties or dialects. Although a number of pioneering works have targeted some Arabic dialects, other dialects remain largely without investigation. A serious bottleneck for studying these dialects is lack of any data that can be exploited in computational models. In this work, we aim to bridge this gap: We present a considerably large dataset of > 1=4 billion tweets representing a wide range of dialects. Our dataset is more nuanced than previously reported work in that it is labeled at the fine-grained level of city. More specifically, the data represent 29 major Arab cities from 10 Arab countries with varying dialects (e.g., Egyptian, Gulf, KSA, Levantine, Yemeni).
@InProceedings{ABDUL-MAGEED18.929, author = {Muhammad Abdul-Mageed and Hassan Alhuzali and Mohamed Elaraby}, title = "{You Tweet What You Speak: A City-Level Dataset of Arabic Dialects}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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