Journal article
Impact of COVID-19: A Text Mining Analysis of Twitter Data in Spanish Language
Hispanic health care international, Vol.19(4), pp.239-245
12/01/2021
DOI: 10.1177/15404153211020453
PMID: 34323101
Abstract
Background: Latino communities in the United States and Latin America are disproportionately affected by the COVID-19 pandemic. We analyzed information shared on Twitter in Spanish language for insights into the public's communication and information needs about the COVID-19 pandemic. Methods: We performed a mixed-methods analysis using a text mining approach. We used SAS Text Miner, an algorithmic-driven statistical program to capture 10,000 tweets posted between June 3, 2020, and June 10, 2020. We used the following search terms to capture relevant Twitter messages in Spanish language: "coronavirus," "covid-19," "corona," and the hash tags "#COVID19" and "#Coronavirus." Key text topics were identified and categorized into themes using an emergent content analysis. Results: We identified 12 text topics and six themes: (1) prevention measures, (2) epidemiology/surveillance, (3) economic impact, (4) optimizing nursing workforce, (5) access to reliable information, and (6) call for a response from the local government. Top trending hashtags from our search included #COVID19 (n = 7,098), #Coronavirus (n = 6,394), and #SNTESALUD (n = 2,598). Conclusions: Spanish-language Tweets related to the COVID-19 pandemic contained information from health departments and labor unions on the surveillance, prevention, and impact of COVID-19. Public health officials should consider increasing their use of Twitter to ensure a wide dissemination of messages about COVID-19 in Spanish outlets.
Details
- Title: Subtitle
- Impact of COVID-19: A Text Mining Analysis of Twitter Data in Spanish Language
- Creators
- Zainab Toteh Osakwe - Adelphi UniversityYamnia Cortes - University of North Carolina at Chapel Hill
- Resource Type
- Journal article
- Publication Details
- Hispanic health care international, Vol.19(4), pp.239-245
- Publisher
- Sage
- DOI
- 10.1177/15404153211020453
- PMID
- 34323101
- ISSN
- 1540-4153
- eISSN
- 1938-8993
- Number of pages
- 7
- Grant note
- R25HL105444 / National Heart, Blood and Lung Institute (NHLBI Behavioral Sleep Medicine [BSM] Program to Increase Diversity in Behavioral Medicine & Sleep Disorders Research [PRIDE])
- Language
- English
- Date published
- 12/01/2021
- Academic Unit
- Nursing
- Record Identifier
- 9984446399802771
Metrics
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