ABSTRACT
While manual analysis of news coverage is difficult and time consuming, methods in natural language processing can be used to uncover otherwise hidden semantics. This work analyses more than 370,000 news articles to explore connections and trends in business decisions and their financial impact during the COVID-19 pandemic. Topic modelling, sentiment analysis and named entity recognition methods are used to identify connections between the articles and the financial performance of selected companies or industries. This report sets out the results of the individual natural language processing methods and the resulting analysis with financial data. Interesting contrasting topics in the media can be filtered out that are associated with the companies with the highest or lowest positive sentiment. This information could be useful to companies to gain an understanding of topics that are currently treated favourably or unfavourably by the media and hence assist with communication strategies and competitive intelligence. © 2022 IEEE.
ABSTRACT
Tolosa-Hunt syndrome (THS) is a rare, idiopathic, non-specific inflammation within the cavernous sinus and/or superior orbital fissure leading to painful ophthalmoplegia. The authors describe the first case of a 12-year-old otherwise healthy girl who presented with painful ophthalmoplegia after a documented COVID-19 infection. Neuroimaging revealed inflammation within the ipsilateral cavernous sinus, Meckel’s cave, and orbital apex. After a comprehensive work-up was negative, the patient experienced prompt clinical and radiographic improvement with high-dose corticosteroids, and a diagnosis of THS was made. © The Author(s) 2022.