In this paper, we give a brief study that allow us to analyze some Arabic tweets posted in the Covid-19 period and classify them into “Positive, Negative and Neutral”. This paper is about our participation on CERIST Natural Language
Processing Challenge. We worked on a dataset that consist of 4800 tuples on which we applied three different approaches “Naive Bayes, Neuron network and Stochastic gradient descent (SGD)” where the last algorithm gave the best result with an accuracy of 91%.

Auteurs : Slimane Arbaoui, Alaa Eddine Belfedhal

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