Scaling up the discovery of hesitancy profiles by identifying the framing of beliefs towards vaccine confidence in Twitter discourse.
Our study focused on the discovery of how vaccine hesitancy is framed in Twitter discourse, allowing us to recognize at-scale all tweets that evoke any of the hesitancy framings as well as the stance of the tweet authors towards the frame. By categorizing the hesitancy framings that propagate misinf...
| Publicado en: | Journal of Behavioral Medicine Vol. 46; no. 1/2; pp. 253 - 276 |
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| Autores principales: | , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=163005081&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 163005081 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01607715 JBM jtl: Journal of Behavioral Medicine issn: 01607715 maglogo: N pubinfo: dt: Apr2023 vid: 46 iid: 1/2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 163005081 157147763 163005081 163005081 10.1007/s10865-022-00328-z 163005081 ppf: 253 ppct: 23 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Scaling up the discovery of hesitancy profiles by identifying the framing of beliefs towards vaccine confidence in Twitter discourse. aug: au: Weinzierl, Maxwell A. Hopfer, Suellen Harabagiu, Sanda M. affil: Department of Computer Science, Human Language Technology Research Institute, University of Texas at Dallas, 75080, Richardson, TX, USA sug: subj: COVID-19 Pandemic COVID-19 Vaccines Vaccination Hesitancy Health Beliefs Attitude to Vaccines Confidence Social Media Natural Language Processing Papillomavirus Vaccine Human Misinformation Trust Morals Pharmaceutical Companies Drug Labeling Health Literacy ab: Our study focused on the discovery of how vaccine hesitancy is framed in Twitter discourse, allowing us to recognize at-scale all tweets that evoke any of the hesitancy framings as well as the stance of the tweet authors towards the frame. By categorizing the hesitancy framings that propagate misinformation, address issues of trust in vaccines, or highlight moral issues or civil rights, we were able to empirically recognize their ontological commitments. Ontological commitments of vaccine hesitancy framings couples with the stance of tweet authors allowed us to identify hesitancy profiles for two most controversial yet effective and underutilized vaccines for which there remains substantial reluctance among the public: the Human Papillomavirus and the COVID-19 vaccines. The discovered hesitancy profiles inform public health messaging approaches to effectively reach Twitter users with promise to shift or bolster vaccine attitudes. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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