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