Dialectal Arabic sentiment analysis based on tree-based pipeline optimization tool

The heavy involvement of the Arabic internet users resulted in spreading data written language and creating a vast research area regarding natural processing (NLP). Sentiment analysis is growing field that great importance to everyone considering high added potential for decision-making predicting upcoming actions using texts produced social networks. used microblogging websites, especially Twitter, highly informal. It not compliant with neither standards nor spelling regulations making it quite challenging automatic machine-learning techniques. In this paper’s scope, we propose new approach based on AutoML methods improve efficiency sentiment classification process dialectal Arabic. This was validated through benchmarks testing three different datasets represent vernacular forms obtained results show presented framework has significantly increased accuracy than similar works literature.