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Understanding COVID-19 News Coverage using Medical NLP

Being a global pandemic, the COVID-19 outbreak received global media attention. In this study, we
analyze news publications from CNN and The Guardian – two of the world’s most influential media
organizations. The dataset includes more than 36,000 articles, analyzed using the clinical and biomedical
Natural Language Processing (NLP) models from the Spark NLP for Healthcare library, which enables
a deeper analysis of medical concepts than previously achieved. The analysis covers key entities and
phrases, observed biases, and change over time in news coverage by correlating mined medical symptoms,
procedures, drugs, and guidance with commonly mentioned demographic and occupational groups.
Another analysis is of extracted Adverse Drug Events about drug and vaccine manufacturers, which
when reported by major news outlets has an impact on vaccine hesitancy

Rule-Based and Pattern Matching for Entity Recognition in Spark NLP

Finding patterns and matching strategies are well-known NLP procedures to extract information from text. Spark NLP library has two annotators that can...