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An analysis of COVID-19 vaccine sentiments and opinions on Twitter.
Yousefinaghani, Samira; Dara, Rozita; Mubareka, Samira; Papadopoulos, Andrew; Sharif, Shayan.
  • Yousefinaghani S; School of Computer Science, University of Guelph, Guelph, Ontario, Canada.
  • Dara R; School of Computer Science, University of Guelph, Guelph, Ontario, Canada. Electronic address: drozita@uoguelph.ca.
  • Mubareka S; Sunnybrook Health Sciences Center, Toronto, Ontario, Canada.
  • Papadopoulos A; Department of Population Medicine, University of Guelph, Guelph, Ontario, Canada.
  • Sharif S; Department of Pathobiology, University of Guelph, Guelph, Ontario, Canada.
Int J Infect Dis ; 108: 256-262, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1244746
ABSTRACT

OBJECTIVE:

We identified public sentiments and opinions toward the COVID-19 vaccines based on the content of Twitter. MATERIALS AND

METHODS:

We retrieved 4,552,652 publicly available tweets posted within the timeline of January 2020 to January 2021. Following extraction, we identified vaccine sentiments and opinions of tweets and compared their progression by time, geographical distribution, main themes, keywords, posts engagement metrics and accounts characteristics.

RESULTS:

We found a slight difference in the prevalence of positive and negative sentiments, with positive being the dominant polarity and having higher engagements. The amount of discussion on vaccine rejection and hesitancy was more than interest in vaccines during the course of the study, but the pattern was different in various countries. We found the accounts producing vaccine opposition content were partly Twitter bots or political activists while well-known individuals and organizations generated the content in favour of vaccination.

CONCLUSION:

Understanding sentiments and opinions toward vaccination using Twitter may help public health agencies to increase positive messaging and eliminate opposing messages in order to enhance vaccine uptake.
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Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Int J Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: J.ijid.2021.05.059

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Int J Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: J.ijid.2021.05.059