Social Media Sentiment about COVID-19 Vaccination Predicts Vaccine Acceptance among Peruvian Social Media Users the Next Day

Ayse D. Lokmanoglu; Erik C. Nisbet; Matthew T. Osborne; Joseph Tien; Sam Malloy; Lourdes Cueva Chacón; Esteban Villa Turek; Rod Abhari

doi:10.3390/vaccines11040817

Social Media Sentiment about COVID-19 Vaccination Predicts Vaccine Acceptance among Peruvian Social Media Users the Next Day

Ayse D. Lokmanoglu^*, Erik C. Nisbet, Matthew T. Osborne, Joseph Tien, Sam Malloy, Lourdes Cueva Chacón, Esteban Villa Turek, Rod Abhari

^*Corresponding author for this work

Communication Studies

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Drawing upon theories of risk and decision making, we present a theoretical framework for how the emotional attributes of social media content influence risk behaviors. We apply our framework to understanding how COVID-19 vaccination Twitter posts influence acceptance of the vaccine in Peru, the country with the highest relative number of COVID-19 excess deaths. By employing computational methods, topic modeling, and vector autoregressive time series analysis, we show that the prominence of expressed emotions about COVID-19 vaccination in social media content is associated with the daily percentage of Peruvian social media survey respondents who are vaccine-accepting over 231 days. Our findings show that net (positive) sentiment and trust emotions expressed in tweets about COVID-19 are positively associated with vaccine acceptance among survey respondents one day after the post occurs. This study demonstrates that the emotional attributes of social media content, besides veracity or informational attributes, may influence vaccine acceptance for better or worse based on its valence.

Original language	English (US)
Article number	817
Journal	Vaccines
Volume	11
Issue number	4
DOIs	https://doi.org/10.3390/vaccines11040817
State	Published - Apr 2023

Funding

This research is based upon a grant award to ECN, JT, and SM from the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via Award # 2021-20102000001 (https://www.iarpa.gov/, accessed on 23 March 2023). The funder had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Keywords

COVID-19
Peru
sentiment analysis
social amplification of risk framework
social media
vaccine acceptance

ASJC Scopus subject areas

Immunology
Pharmacology
Drug Discovery
Infectious Diseases
Pharmacology (medical)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/vaccines11040817

Cite this

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title = "Social Media Sentiment about COVID-19 Vaccination Predicts Vaccine Acceptance among Peruvian Social Media Users the Next Day",

abstract = "Drawing upon theories of risk and decision making, we present a theoretical framework for how the emotional attributes of social media content influence risk behaviors. We apply our framework to understanding how COVID-19 vaccination Twitter posts influence acceptance of the vaccine in Peru, the country with the highest relative number of COVID-19 excess deaths. By employing computational methods, topic modeling, and vector autoregressive time series analysis, we show that the prominence of expressed emotions about COVID-19 vaccination in social media content is associated with the daily percentage of Peruvian social media survey respondents who are vaccine-accepting over 231 days. Our findings show that net (positive) sentiment and trust emotions expressed in tweets about COVID-19 are positively associated with vaccine acceptance among survey respondents one day after the post occurs. This study demonstrates that the emotional attributes of social media content, besides veracity or informational attributes, may influence vaccine acceptance for better or worse based on its valence.",

keywords = "COVID-19, Peru, sentiment analysis, social amplification of risk framework, social media, vaccine acceptance",

author = "Lokmanoglu, {Ayse D.} and Nisbet, {Erik C.} and Osborne, {Matthew T.} and Joseph Tien and Sam Malloy and {Cueva Chac{\'o}n}, Lourdes and {Villa Turek}, Esteban and Rod Abhari",

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doi = "10.3390/vaccines11040817",

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AU - Lokmanoglu, Ayse D.

AU - Nisbet, Erik C.

AU - Osborne, Matthew T.

AU - Tien, Joseph

AU - Malloy, Sam

AU - Cueva Chacón, Lourdes

AU - Villa Turek, Esteban

AU - Abhari, Rod

PY - 2023/4

Y1 - 2023/4

N2 - Drawing upon theories of risk and decision making, we present a theoretical framework for how the emotional attributes of social media content influence risk behaviors. We apply our framework to understanding how COVID-19 vaccination Twitter posts influence acceptance of the vaccine in Peru, the country with the highest relative number of COVID-19 excess deaths. By employing computational methods, topic modeling, and vector autoregressive time series analysis, we show that the prominence of expressed emotions about COVID-19 vaccination in social media content is associated with the daily percentage of Peruvian social media survey respondents who are vaccine-accepting over 231 days. Our findings show that net (positive) sentiment and trust emotions expressed in tweets about COVID-19 are positively associated with vaccine acceptance among survey respondents one day after the post occurs. This study demonstrates that the emotional attributes of social media content, besides veracity or informational attributes, may influence vaccine acceptance for better or worse based on its valence.

AB - Drawing upon theories of risk and decision making, we present a theoretical framework for how the emotional attributes of social media content influence risk behaviors. We apply our framework to understanding how COVID-19 vaccination Twitter posts influence acceptance of the vaccine in Peru, the country with the highest relative number of COVID-19 excess deaths. By employing computational methods, topic modeling, and vector autoregressive time series analysis, we show that the prominence of expressed emotions about COVID-19 vaccination in social media content is associated with the daily percentage of Peruvian social media survey respondents who are vaccine-accepting over 231 days. Our findings show that net (positive) sentiment and trust emotions expressed in tweets about COVID-19 are positively associated with vaccine acceptance among survey respondents one day after the post occurs. This study demonstrates that the emotional attributes of social media content, besides veracity or informational attributes, may influence vaccine acceptance for better or worse based on its valence.

KW - COVID-19

KW - Peru

KW - sentiment analysis

KW - social amplification of risk framework

KW - social media

KW - vaccine acceptance

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Social Media Sentiment about COVID-19 Vaccination Predicts Vaccine Acceptance among Peruvian Social Media Users the Next Day

Abstract

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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