Abstract
Social media platforms have become one of the most powerful tools for organizations and individuals to publish news and express thoughts or feelings. With the increasingly enormous number of internet users in Saudi Arabia, the need raised to analyze Arabic posts. Since the emergence of COVID-19 in the latest 2019, it lefts economies and businesses counting the cost while governments fight the spread of the virus with new compartmentalization measures. Keeping in view the importance of quick and timely data analysis and sharing for policy actions, Artificial intelligence (AI) has played a crucial role in facilitating the exchange of views and information between scientists and decision-makers during the Coronavirus pandemic, and they continue to do so. This work mined to these content-related tweets to see how people's feelings and expressions are changing. The results of this analysis can be used with integration with several IoT technologies to reduce the impact of covid-19 and drive new decisions in this field. For this goal, we proposed a Machine Learning (ML) models that can classify both of the sentiment and topic of Modern Standard Arabic (MSA) tweets and achieve high accuracy results.