Abstract
Covid-19 or Coronavirus is the most popular common term in recent time. The SARS-CoV-2 virus caused a pandemic of respiratory disturbance which is named as COVID-19. The coronavirus is outspread through drop liquids as well as virus bits which are released into the air by an infected person’s breathing, coughing or sneezing. This pandemic has become a great death threat to the people, even the children too. It’s quite unexpected that some corrupted individuals spread false or fake news to disrupt the social balance. Due to the news misguidance, numerous people have been misled for taking proper care. For this issue, we have analyzed some machine learning techniques, among them, an ensemble method Random forest has gained 90% with the best exactitude. The other models Naive Bayes got 85%, as well as another ensemble method created by Naive Bayes with Support Vector Machine (SVM), gained the exactitude as 88%.
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Ghosh, P., Raihan, M., Hassan, M.M., Akter, L., Zaman, S., Awal, M.A. (2022). Fake News Detection of COVID-19 Using Machine Learning Techniques. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing & Optimization. ICO 2021. Lecture Notes in Networks and Systems, vol 371. Springer, Cham. https://doi.org/10.1007/978-3-030-93247-3_46
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DOI: https://doi.org/10.1007/978-3-030-93247-3_46
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