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The global world is crossing a pandemic situation where this is acatastrophic outbreak of Respiratory Syndrome recognized as COVID-19. This is aglobal threat all over the 212 countries that people every day meet with mightysituations. On the contrary, thousands of infected people live rich inmountains. Mental health is also affected by this worldwide coronavirussituation. Due to this situation online sources made a communicative place thatcommon people shares their opinion in any agenda. Such as affected news relatedpositive and negative, financial issues, country and family crisis, lack ofimport and export earning system etc. different kinds of circumstances arerecent trendy news in anywhere. Thus, vast amounts of text are produced withinmoments therefore, in subcontinent areas the same as situation in othercountries and peoples opinion of text and situation also same but the languageis different. This article has proposed some specific inputs along with Banglatext comments from individual sources which can assure the goal of illustrationthat machine learning outcome capable of building an assistive system. Opinionmining assistive system can be impactful in all language preferences possible.To the best of our knowledge, the article predicted the Bangla input text onCOVID-19 issues proposed ML algorithms and deep learning models analysis alsocheck the future reachability with a comparative analysis. Comparative analysisstates a report on text prediction accuracy is 91% along with ML algorithms and79% along with Deep Learning Models.

An Opinion Mining of Text in COVID-19 Issues along with Comparative Study in ML, BERT & RNN