Evidence map›Paper›PMID 35649182›Full record

ArticleJournal of medical Internet research2022

The Effect of Fear of Infection and Sufficient Vaccine Reservation Information on Rapid COVID-19 Vaccination in Japan: Evidence From a Retrospective Twitter Analysis.

Qian Niu, Junyu Liu, Masaya Kato, Momoko Nagai-Tanima, Tomoki Aoyama

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2022. 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
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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 12 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Qian Niu *Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan.ORCID 0000-0001-7139-384X
Junyu Liu *Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto, Japan.ORCID 0000-0001-6232-4199
Masaya KatoDepartment of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan.ORCID 0000-0001-5589-2665
Momoko Nagai-TanimaDepartment of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan.ORCID 0000-0003-3972-8800
Tomoki AoyamaDepartment of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan.ORCID 0000-0003-3512-054X
Kyoto University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe global public health and socioeconomic impacts of the COVID-19 pandemic have been substantial, rendering herd immunity by COVID-19 vaccination an important factor for protecting people and retrieving the economy. Among all the countries, Japan became one of the countries with the highest COVID-19 vaccination rates in several months, although vaccine confidence in Japan is the lowest worldwide.

objectiveWe attempted to find the reasons for rapid COVID-19 vaccination in Japan given its lowest vaccine confidence levels worldwide, through Twitter analysis.

methodsWe downloaded COVID-19-related Japanese tweets from a large-scale public COVID-19 Twitter chatter data set within the timeline of February 1 and September 30, 2021. The daily number of vaccination cases was collected from the official website of the Prime Minister's Office of Japan. After preprocessing, we applied unigram and bigram token analysis and then calculated the cross-correlation and Pearson correlation coefficient (r) between the term frequency and daily vaccination cases. We then identified vaccine sentiments and emotions of tweets and used the topic modeling to look deeper into the dominant emotions.

resultsWe selected 190,697 vaccine-related tweets after filtering. Through n-gram token analysis, we discovered the top unigrams and bigrams over the whole period. In all the combinations of the top 6 unigrams, tweets with both keywords "reserve" and "venue" showed the largest correlation with daily vaccination cases (r=0.912; P<.001). On sentiment analysis, negative sentiment overwhelmed positive sentiment, and fear was the dominant emotion across the period. For the latent Dirichlet allocation model on tweets with fear emotion, the two topics were identified as "infect" and "vaccine confidence." The expectation of the number of tweets generated from topic "infect" was larger than that generated from topic "vaccine confidence."

conclusionsOur work indicates that awareness of the danger of COVID-19 might increase the willingness to get vaccinated. With a sufficient vaccine supply, effective delivery of vaccine reservation information may be an important factor for people to get vaccinated. We did not find evidence for increased vaccine confidence in Japan during the period of our study. We recommend policy makers to share accurate and prompt information about the infectious diseases and vaccination and to make efforts on smoother delivery of vaccine reservation information.

Indexed as

COVID-19Social MediaCOVID-19 VaccinesFearHumansJapanPandemicsRetrospective StudiesVaccinationCOVID-19 VaccinesCOVID-19Japansocial mediatext miningvaccine hesitancy

Identifiers

PMID35649182
PMCPMC9186499
OpenAlexW4281627355

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.