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The COVID-19 pandemic has put immense pressure on health systems which arefurther strained due to the misinformation surrounding it. Under such asituation, providing the right information at the right time is crucial. Thereis a growing demand for the management of information spread using ArtificialIntelligence. Hence, we have exploited the potential of Natural LanguageProcessing for identifying relevant information that needs to be disseminatedamongst the masses. In this work, we present a novel Cross-lingual NaturalLanguage Processing framework to provide relevant information by matching dailynews with trusted guidelines from the World Health Organization. The proposedpipeline deploys various techniques of NLP such as summarizers, wordembeddings, and similarity metrics to provide users with news articles alongwith a corresponding healthcare guideline. A total of 36 models were evaluatedand a combination of LexRank based summarizer on Word2Vec embedding with WordMover distance metric outperformed all other models. This novel open-sourceapproach can be used as a template for proactive dissemination of relevanthealthcare information in the midst of misinformation spread associated withepidemics.

A Cross-lingual Natural Language Processing Framework for Infodemic Management