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- Title
Discovering topics in Twitter about the COVID-19 outbreak in Spain.
- Authors
Agüero-Torales, Marvin M.; Vilares, David; López-Herrera, Antonio G.
- Abstract
In this work, we apply topic modeling to study what users have been discussing in Twitter during the beginning of the COVID-19 pandemic. More particularly, we explore the period of time that includes three differentiated phases of the COVID-19 crisis in Spain: the pre-crisis time, the outbreak, and the beginning of the lockdown. To do so, we first collect a large corpus of Spanish tweets and clean them. Then, we cluster the tweets into topics using a Latent Dirichlet Allocation model, and define generative and discriminative routes to later extract the most relevant keywords and sentences for each topic. Finally, we provide an exhaustive qualitative analysis about how such topics correspond to the situation in Spain at different stages of the crisis.
- Subjects
SPAIN; COVID-19 pandemic; THESIS statements (Rhetoric); STAY-at-home orders
- Publication
Procesamiento del Lenguaje Natural, 2021, Vol 66, p177
- ISSN
1135-5948
- Publication type
Article
- DOI
10.26342/2021-66-15