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Natural Language Processing (NLP) is today a very active field of researchand innovation. Many applications need however big sets of data for supervisedlearning, suitably labelled for the training purpose. This includesapplications for the Arabic language and its national dialects. However, suchopen access labeled data sets in Arabic and its dialects are lacking in theData Science ecosystem and this lack can be a burden to innovation and researchin this field. In this work, we present an open data set of social data contentin several Arabic dialects. This data was collected from the Twitter socialnetwork and consists on +50K twits in five (5) national dialects. Furthermore,this data was labeled for several applications, namely dialect detection, topicdetection and sentiment analysis. We publish this data as an open access datato encourage innovation and encourage other works in the field of NLP forArabic dialects and social media. A selection of models were built using thisdata set and are presented in this paper along with their performances.

An open access NLP dataset for Arabic dialects : Data collection, labeling, and model construction