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Ghana by stephen mensah is a document available to read on EtoBox.

This conference paper analyzes public sentiments expressed in tweets during the COVID-19 lockdown in Ghana using natural language processing and machine learning techniques. The study found that while negative sentiments were predominant, there were also significant positive sentiments at times. The support vector machine (SVM) algorithm was identified as the most effective for sentiment classification, with the findings aimed at guiding policymakers in managing public sentiments during pandemics.

Author

stephen mensah

Language

EN