Evidence map›Paper›PMID 35746490›Full record

ArticleVaccines2022

New Wave of COVID-19 Vaccine Opinions in the Month the 3rd Booster Dose Arrived.

Camelia Delcea, Liviu-Adrian Cotfas, Liliana Crăciun, Anca Gabriela Molănescu

Open access · goldAbstract read
In one paragraph

Article in Vaccines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 16% of its field
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

2 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
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

4 authors at 1 institution in 1 country.

Camelia DelceaDepartment of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania.ORCID 0000-0003-3589-1969
Liviu-Adrian CotfasDepartment of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania.ORCID 0000-0002-4192-183X
Liliana CrăciunDepartment of Economics and Economic Policies, Bucharest University of Economic Studies, 010374 Bucharest, Romania.
Anca Gabriela MolănescuDepartment of Economics and Economic Policies, Bucharest University of Economic Studies, 010374 Bucharest, Romania.
Bucharest University of Economic Studies · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vaccination has been proposed as one of the most effective methods to combat the COVID-19 pandemic. Since the day the first vaccine, with an efficiency of more than 90%, was announced, the entire vaccination process and its possible consequences in large populations have generated a series of discussions on social media. Whereas the opinions triggered by the administration of the initial COVID-19 vaccine doses have been discussed in depth in the scientific literature, the approval of the so-called 3rd booster dose has only been analyzed in country-specific studies, primarily using questionnaires. In this context, the present paper conducts a stance analysis using a transformer-based deep learning model on a dataset containing 3,841,594 tweets in English collected between 12 July 2021 and 11 August 2021 (the month in which the 3rd dose arrived) and compares the opinions (

Indexed as

COVID-19 vaccinationdeep learningnatural language processingopinion miningstance analysis

Identifiers

PMID35746490
PMCPMC9228932
OpenAlexW4281989533

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.