  Tunisians on social media tend to express themselves in their local dialect
using Latin script (TUNIZI). This raises an additional challenge to the process
of exploring and recognizing online opinions. To date, very little work has
addressed TUNIZI sentiment analysis due to scarce resources for training an
automated system. In this paper, we focus on the Tunisian dialect sentiment
analysis used on social media. Most of the previous work used machine learning
techniques combined with handcrafted features. More recently, Deep Neural
Networks were widely used for this task, especially for the English language.
In this paper, we explore the importance of various unsupervised word
representations (word2vec, BERT) and we investigate the use of Convolutional
Neural Networks and Bidirectional Long Short-Term Memory. Without using any
kind of handcrafted features, our experimental results on two publicly
available datasets showed comparable performances to other languages.
