Digital Narratives of COVID-19 on Twitter: From Data to Interpretation

Authors

  • Susanna Alles Torrent University of Miami
  • Gimena del Rio Riande CONICET
  • Romina De León CONICET
  • Marisol Fila University of Michigan
  • Nidia Hernández CONICET
  • Jerry Bonnell University of Miami
  • Dieyun Song University of Miami

DOI:

https://doi.org/10.24215/27187470e002

Keywords:

Twitter, Data, Narratives, Data Mining, Sentiment Analysis

Abstract

The bilingual project Digital Narratives of COVID-19 brings together researchers, programmers, and students from the University of Miami and CONICET (Argentina). DHCovid aims to analyze and interpret Twitter data (in English and Spanish) on the SARS-CoV -2 global pandemic from the end of April 2020 to May 2021, through quantitative methods and tools used in the field of DH. This article explores the different methods and tools that the project has used, from basic search platforms and semi-automated textmining to more complex and more or less supervised ones. The paper additionally discusses how this set of tweets was collected to study the narratives and emerging issues about the pandemic in South Florida and specific Spanish-speaking countries (Argentina, Mexico, Peru, Colombia, Ecuador, Spain). Furthermore, it presents the GitHub and Zenodo data repository as well as some of the tools developed by the project.
Finally, work with data mining, frequency analysis of terms and concordances, and topic modeling will be exhibited.

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Published

2020-12-15

How to Cite

Alles Torrent, S., del Rio Riande, G., De León, R., Fila, M., Hernández, N., Jerry Bonnell, & Song, D. (2020). Digital Narratives of COVID-19 on Twitter: From Data to Interpretation . Publicaciones De La Asociación Argentina De Humanidades Digitales, 1, e002. https://doi.org/10.24215/27187470e002