We present a first approximation to the quantification of social representations about the COVID-19, using news comments. A web crawler was developed to construct the dataset of reader’s comments. We detect relevant topics in the dataset using Latent Dirichlet Allocation, and analyze its evolution during time. Finally, we show a first prototype to the prediction of the majority topics, using FastText.
free text keywords: Ciencias Informáticas, NLP, News comments, COVID-19, Social representations