Using MT for multilingual covid-19 case load prediction from social media texts

Maja Popovic, Vasudevan Nedumpozhimana, Meegan Gower, Sneha Rautmare, Nishtha Jain, John D. Kelleher

Abstract: In the context of an epidemiological study involving multilingual social media, this paper reports on the ability of machine translation systems to preserve content relevant for a document classification task designed to determine whether the social media text is related to covid. The results indicate that machine translation does provide a feasible basis for scaling epidemiological social media surveillance to multiple languages. Moreover, a qualitative error analysis revealed that the majority of classification errors are not caused by MT errors.