Nowadays, sentiment analysis is one of the most crucial research field of Natural Language Processing (NLP) and it is widely applied in a variety of applications such as marketing and politics. However, the Arabic language still lacks sufficient language resources to enable the tasks of opinion and emotion analysis comparing to other language such as English. Additionally, manual annotation requires a lot of effort and time. In this paper, we address this problem and propose a novel automated annotation platform for sentiment analysis called AlgBERT, by providing annotated corpus and using deep learning technology that includes many automatic natural language processing algorithms, which is the basis for text classification and opinion analysis. We suggest using BERT model as a method, it is the abbreviation of Bidirectional Encoder Representations from Transformers, as it is one of the most effective technology in terms of results in different world languages. We used around of 54000 comments collected from social networking (Twitter, YouTube) written in Arabic and Algerian dialect. Our AlgBERT system obtained excellent results with an accuracy of 92.6% and this considers as one of the best results for opinion analysis in Algerian dialect.