Evidence map›Paper›PMID 35635593›Full record

ArticleJournal of behavioral medicine2023

Scaling up the discovery of hesitancy profiles by identifying the framing of beliefs towards vaccine confidence in Twitter discourse.

Maxwell A Weinzierl, Suellen Hopfer, Sanda M Harabagiu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of behavioral medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Maxwell A WeinzierlDepartment of Computer Science, Human Language Technology Research Institute, University of Texas at Dallas, Richardson, TX, 75080, USA. maxwell.weinzierl@utdallas.edu.ORCID 0000-0002-8049-7453
Suellen HopferDepartment of Health Society and Behavior, Department of Pediatrics, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, Irvine, CA, 92617, USA.
Sanda M HarabagiuDepartment of Computer Science, Human Language Technology Research Institute, University of Texas at Dallas, Richardson, TX, 75080, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19Social MediaVaccinesAttitude to HealthCOVID-19 VaccinesHumansVaccinationCOVID-19 VaccinesVaccinesCOVID-19HPVMisinformationMoral foundationsNatural language processingQuestion answer frameworkSocial mediaTrustTwitterVaccine confidenceVaccine hesitancy

Identifiers

PMID35635593
PMCPMC9148945

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.