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Evaluating Voice Assistants' Responses to COVID-19 Vaccination in Portuguese: Quality Assessment.

JMIR human factorsยท2022
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Comparing News Articles and Tweets About COVID-19 in Brazil: Sentiment Analysis and Topic Modeling Approach.

Tiago de Melo1, Carlos M S Figueiredo1

  • 1Intelligent Systems Laboratory, Superior School of Technology, Amazonas State University, Manaus, Brazil.

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|January 22, 2021
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Summary

This study developed a method to analyze COVID-19 discussions on social media and news in Brazil. The analysis revealed public sentiment and key themes, aiding in understanding the pandemic's impact.

Keywords:
BrazilCOVID-19Twitterentity recognitioninfodemiologymonitoringnewssentiment analysissocial mediatext analysistopic modeling

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Area of Science:

  • Computational Social Science
  • Public Health Informatics
  • Natural Language Processing

Background:

  • The COVID-19 pandemic significantly impacts global populations.
  • Monitoring online news and social media is crucial for understanding pandemic-related public discourse.

Purpose of the Study:

  • To present a methodology for capturing and analyzing main subjects and themes in news and social media.
  • To apply this methodology to analyze the impact of the COVID-19 pandemic in Brazil.

Main Methods:

  • Utilized topic modeling, entity recognition, and sentiment analysis for text analysis.
  • Compared discussions on Twitter and news media, focusing on Brazilian Portuguese content.
  • Visualized the evolution and impact of the pandemic through data analysis.

Main Results:

  • Analyzed 18,413 news articles and 1,597,934 tweets from Brazil.
  • The methodology enhanced topic sentiment analysis for better internet media monitoring.
  • Identified similar topic coverage but differing theme distribution and entity diversity between Twitter and news media.
  • Observed negative sentiment towards political themes and high political polarization related to specific drug mentions.

Conclusions:

  • Successfully identified key themes and evolving sentiments in news and social media during the pandemic.
  • The findings provide insights into public concerns and support decision-making for authorities.
  • The developed tool offers a valuable approach for monitoring public discourse during health crises.