Tags

Type your tag names separated by a space and hit enter

COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies.
JMIR Public Health Surveill. 2021 11 17; 7(11):e30642.JP

Abstract

BACKGROUND

False claims about COVID-19 vaccines can undermine public trust in ongoing vaccination campaigns, posing a threat to global public health. Misinformation originating from various sources has been spreading on the web since the beginning of the COVID-19 pandemic. Antivaccine activists have also begun to use platforms such as Twitter to promote their views. To properly understand the phenomenon of vaccine hesitancy through the lens of social media, it is of great importance to gather the relevant data.

OBJECTIVE

In this paper, we describe a data set of Twitter posts and Twitter accounts that publicly exhibit a strong antivaccine stance. The data set is made available to the research community via our AvaxTweets data set GitHub repository. We characterize the collected accounts in terms of prominent hashtags, shared news sources, and most likely political leaning.

METHODS

We started the ongoing data collection on October 18, 2020, leveraging the Twitter streaming application programming interface (API) to follow a set of specific antivaccine-related keywords. Then, we collected the historical tweets of the set of accounts that engaged in spreading antivaccination narratives between October 2020 and December 2020, leveraging the Academic Track Twitter API. The political leaning of the accounts was estimated by measuring the political bias of the media outlets they shared.

RESULTS

We gathered two curated Twitter data collections and made them publicly available: (1) a streaming keyword-centered data collection with more than 1.8 million tweets, and (2) a historical account-level data collection with more than 135 million tweets. The accounts engaged in the antivaccination narratives lean to the right (conservative) direction of the political spectrum. The vaccine hesitancy is fueled by misinformation originating from websites with already questionable credibility.

CONCLUSIONS

The vaccine-related misinformation on social media may exacerbate the levels of vaccine hesitancy, hampering progress toward vaccine-induced herd immunity, and could potentially increase the number of infections related to new COVID-19 variants. For these reasons, understanding vaccine hesitancy through the lens of social media is of paramount importance. Because data access is the first obstacle to attain this goal, we published a data set that can be used in studying antivaccine misinformation on social media and enable a better understanding of vaccine hesitancy.

Links

PMC Free PDF

Authors+Show Affiliations

Muric G
Information Sciences Institute, University of Southern California, Marina del Rey, CA, United States.
Wu Y
Information Sciences Institute, University of Southern California, Marina del Rey, CA, United States.
Ferrara E
Information Sciences Institute, University of Southern California, Marina del Rey, CA, United States. Department of Computer Science, University of Southern California, Los Angeles, CA, United States. Annenberg School for Communication and Journalism, University of Southern California, Los Angeles, CA, United States.

MeSH

COVID-19COVID-19 VaccinesCommunicationHumansPandemicsSARS-CoV-2Social Media

Pub Type(s)

Journal Article

Language

eng

PubMed ID

34653016

Citation

Muric, Goran, et al. "COVID-19 Vaccine Hesitancy On Social Media: Building a Public Twitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies." JMIR Public Health and Surveillance, vol. 7, no. 11, 2021, pp. e30642.
Muric G, Wu Y, Ferrara E. COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies. JMIR Public Health Surveill. 2021;7(11):e30642.
Muric, G., Wu, Y., & Ferrara, E. (2021). COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies. JMIR Public Health and Surveillance, 7(11), e30642. https://doi.org/10.2196/30642
Muric G, Wu Y, Ferrara E. COVID-19 Vaccine Hesitancy On Social Media: Building a Public Twitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies. JMIR Public Health Surveill. 2021 11 17;7(11):e30642. PubMed PMID: 34653016.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies. AU - Muric,Goran, AU - Wu,Yusong, AU - Ferrara,Emilio, Y1 - 2021/11/17/ PY - 2021/05/23/received PY - 2021/10/12/accepted PY - 2021/08/26/revised PY - 2021/10/16/pubmed PY - 2021/11/23/medline PY - 2021/10/15/entrez KW - COVID-19 KW - COVID-19 vaccines KW - SARS-CoV-2 KW - Twitter KW - conspiracy KW - dataset KW - hesitancy KW - misinformation KW - network analysis KW - public health KW - social media KW - trust KW - utilization KW - vaccine KW - vaccine hesitancy SP - e30642 EP - e30642 JF - JMIR public health and surveillance JO - JMIR Public Health Surveill VL - 7 IS - 11 N2 - BACKGROUND: False claims about COVID-19 vaccines can undermine public trust in ongoing vaccination campaigns, posing a threat to global public health. Misinformation originating from various sources has been spreading on the web since the beginning of the COVID-19 pandemic. Antivaccine activists have also begun to use platforms such as Twitter to promote their views. To properly understand the phenomenon of vaccine hesitancy through the lens of social media, it is of great importance to gather the relevant data. OBJECTIVE: In this paper, we describe a data set of Twitter posts and Twitter accounts that publicly exhibit a strong antivaccine stance. The data set is made available to the research community via our AvaxTweets data set GitHub repository. We characterize the collected accounts in terms of prominent hashtags, shared news sources, and most likely political leaning. METHODS: We started the ongoing data collection on October 18, 2020, leveraging the Twitter streaming application programming interface (API) to follow a set of specific antivaccine-related keywords. Then, we collected the historical tweets of the set of accounts that engaged in spreading antivaccination narratives between October 2020 and December 2020, leveraging the Academic Track Twitter API. The political leaning of the accounts was estimated by measuring the political bias of the media outlets they shared. RESULTS: We gathered two curated Twitter data collections and made them publicly available: (1) a streaming keyword-centered data collection with more than 1.8 million tweets, and (2) a historical account-level data collection with more than 135 million tweets. The accounts engaged in the antivaccination narratives lean to the right (conservative) direction of the political spectrum. The vaccine hesitancy is fueled by misinformation originating from websites with already questionable credibility. CONCLUSIONS: The vaccine-related misinformation on social media may exacerbate the levels of vaccine hesitancy, hampering progress toward vaccine-induced herd immunity, and could potentially increase the number of infections related to new COVID-19 variants. For these reasons, understanding vaccine hesitancy through the lens of social media is of paramount importance. Because data access is the first obstacle to attain this goal, we published a data set that can be used in studying antivaccine misinformation on social media and enable a better understanding of vaccine hesitancy. SN - 2369-2960 UR - https://www.unboundmedicine.com/medline/citation/34653016/COVID_19_Vaccine_Hesitancy_on_Social_Media:_Building_a_Public_Twitter_Data_Set_of_Antivaccine_Content_Vaccine_Misinformation_and_Conspiracies_ DB - PRIME DP - Unbound Medicine ER -