Abstract
Vaccination is an important subject of discussion adjacent to the COVID-19 pandemic. Sentiments generated online by this topic are worth analyzing using opinion mining tools, and it is interesting to do so in online content written in an under-researched language, like Romanian. For this reason, we modified and enlarged an existing sentiment analysis dataset comprised of Romanian tweets labeled as negative or positive. The resulting dataset, SART (Sentiment Analysis from Romanian Tweets), comprised of three classes (positive, negative, and neutral) containing 1300 Romanian tweets each, was used to train two different sentiment analysis models: a fastText-based one and a fine-tuned BERT model. We further show the usefulness of the sentiment analysis model by analyzing the sentiment of Romanian tweets regarding vaccination using a corpus created and collected by the authors between January 2021 and February 2022 (COVIDSentiRo).
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