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Very large numbers of M-pox cases have, since the start of May 2022, beenreported in non-endemic countries leading many to fear that the M-pox Outbreakwould rapidly transition into another pandemic, while the COVID-19 pandemicravages on. Given the similarities of M-pox with COVID-19, we chose to test theperformance of COVID-19 models trained on South African twitter data on ahand-labelled M-pox dataset before and after fine-tuning. More than 20kM-pox-related tweets from South Africa were hand-labelled as being eitherpositive, negative or neutral. After fine-tuning these COVID-19 models on theM-pox dataset, the F1-scores increased by more than 8% falling just short of70%, but still outperforming state-of-the-art models and well-knownclassification algorithms. An LDA-based topic modelling procedure was used tocompare the miss-classified M-pox tweets of the original COVID-19 RoBERTa modelwith its fine-tuned version, and from this analysis, we were able to drawconclusions on how to build more sophisticated models.

COVID-19 South African Vaccine Hesitancy Models Show Boost in Performance Upon Fine-Tuning on M-pox Tweets