Evidence map›Paper›PMID 35920771›Full record

ArticleHuman vaccines & immunotherapeutics2022

Public attitudes on social media toward vaccination before and during the COVID-19 pandemic.

Uzair Shah, Md Rafiul Biswas, Raian Ali, Hazrat Ali, Zubair Shah

Abstract read
In one paragraph

Article in Human vaccines & immunotherapeutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Uzair ShahCollege of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Md Rafiul BiswasCollege of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Raian AliCollege of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Hazrat AliCollege of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Zubair ShahCollege of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the success of COVID-19 vaccines in clinical trials, vaccination programs are being administered for the population with the hopes of herd immunity. However, the success of any vaccination program depends on the percentage of people willing to get vaccination which is influenced by social, economic, demographic, and vaccine-specific factors. Thus, it is important to understand public attitudes and perceptions toward vaccination. This study aims to measure public attitude toward vaccines and vaccinations before and during the COVID-19 pandemic, using public data from Twitter. A total of 880,586 tweets for 57,529 unique users were included in the study. Most of the tweets were posted in five languages: French, English, Swedish, Dutch, and Italian. These tweets were divided into two time periods: before COVID-19 (T1) and during COVID-19 (T2). This study observed the shift in the sentiments of the public attitude toward vaccines before and during COVID-19 pandemic. Both positive and negative shifts in sentiments were observed for the users of various languages but shifts toward positive sentiments were more prominent during the COVID-19 pandemic.

Indexed as

COVID-19Social MediaVaccinesCOVID-19 VaccinesHumansPandemicsVaccinationCOVID-19 VaccinesVaccinesCOVID-19sentiment analysissocial mediavaccine

Identifiers

PMID35920771
PMCPMC9746453

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.