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The purpose of this study is to analyse COVID-19 related news publishedacross different geographical places, in order to gain insights in reportingdifferences. The COVID-19 pandemic had a major outbreak in January 2020 and wasfollowed by different preventive measures, lockdown, and finally by the processof vaccination. To date, more comprehensive analysis of news related toCOVID-19 pandemic are missing, especially those which explain what aspects ofthis pandemic are being reported by newspapers inserted in different economiesand belonging to different political alignments. Since LDA is often lesscoherent when there are news articles published across the world about an eventand you look answers for specific queries. It is because of having semanticallydifferent content. To address this challenge, we performed pooling of newsarticles based on information retrieval using TF-IDF score in a data processingstep and topic modeling using LDA with combination of 1 to 6 ngrams. We usedVADER sentiment analyzer to analyze the differences in sentiments in newsarticles reported across different geographical places. The novelty of thisstudy is to look at how COVID-19 pandemic was reported by the media, providinga comparison among countries in different political and economic contexts. Ourfindings suggest that the news reporting by newspapers with different politicalalignment support the reported content. Also, economic issues reported bynewspapers depend on economy of the place where a newspaper resides.

Political and Economic Patterns in COVID-19 News: From Lockdown to Vaccination