Tunisian Arabic (TA) is a morphologically and syntactically rich dialect, which presents an interesting challenge for Natural Language Processing (NLP) tasks such as part-of-speech tagging, parsing, semantic analysis, etc. It is classified as a low-resourced language. Tunisians use it in daily life communication, social media exchanges, etc. In this paper, we focus on Tunisian Arabic linguistic resources and tools creation. We present the creation and generation of Tunisian treebank and parser for social media texts. We use an existing state-of-the-art parser to build this treebank. Then, we investigate the effects of different data sizes and different combinations of Tunisian dialect forms in automatic parsing.