TunRoBERTa: A Tunisian Robustly Optimized BERT Approach Model for Sentiment Analysis

Sentiment Analysis has grown in importance and popularity due to the proliferation of microblogging sites and the increase in posted comments, tweets, and posts, as it allows for the prediction of people’s feelings, thoughts, impressions, and opinions. Sentiment analysis is regarded as one of the most active research areas in NLP. As a result, this tool has piqued the interest of marketing and business firms, government organizations, and society as a whole. Based on that, we propose a Tunisian model in this paper. A robustly optimized BERT approach was used to establish sentiment classification from the Tunisian corpus.