Evidence map›Paper›PMID 29911966›Full record

ArticleThe Permanente journal2018

Sentiment, Contents, and Retweets: A Study of Two Vaccine-Related Twitter Datasets.

Elizabeth B Blankenship, Mary Elizabeth Goff, Jinging Yin, Zion Tsz Ho Tse, King-Wa Fu, Hai Liang, Nitin Saroha, Isaac Chun-Hai Fung

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PubMed Full text at PMC Publisher
In one paragraph

Article in The Permanente journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 3 pooled it
–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

47 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  3. Analysis of the Anti-Vaccine Movement in Social Networks: A Systematic Review.International journal of environmental research and public health · 2020
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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

8 authors.

Elizabeth B BlankenshipGraduate Student in Epidemiology and Environmental Health Sciences at the Jiann-Ping Hsu College of Public Health at Georgia Southern University in Statesboro. eb03763@georgiasouthern.edu.
Mary Elizabeth GoffGraduate Student in Epidemiology and Environmental Health Sciences at the Jiann-Ping Hsu College of Public Health at Georgia Southern University in Statesboro. eg01587@georgiasouthern.edu.
Jinging YinAssistant Professor of Biostatistics at the Jiann-Ping Hsu College of Public Health at Georgia Southern University in Statesboro. jyin@georgiasouthern.edu.
Zion Tsz Ho TseAssociate Professor in the School of Electrical and Computer Engineering at the College of Engineering at the University of Georgia in Athens. ziontse@uga.edu.
King-Wa FuAssociate Professor at the Journalism and Media Studies Centre at the University of Hong Kong and a Visiting Associate Professor at the Massachusetts Institute of Technology Media Lab in Cambridge. kwfu@hku.hk.
Hai LiangAssistant Professor in the School of Journalism and Communication at the Chinese University of Hong Kong. hailiang@cuhk.edu.hk.
Nitin SarohaGraduate Student in Computer Science at the University of Georgia in Athens. ns10510@uga.edu.
Isaac Chun-Hai FungAssistant Professor in Epidemiology and Environmental Health Sciences at the Jiann-Ping Hsu College of Public Health at Georgia Southern University in Statesboro. cfung@georgiasouthern.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSocial media platforms are important channels through which health education about the utility and safety of vaccination is conducted.

objectiveTo investigate if tweets with different sentiments toward vaccination and different contents attract different levels of Twitter users' engagement (retweets).

methodsA stratified random sample (N = 1425) of 142,891 #vaccine tweets (February 4, 2010, to November 10, 2016) was manually coded. All 201 tweets with 100 or more retweets from 194,259 #vaccineswork tweets (January 1, 2014, to April 30, 2015) were manually coded. Regression models were applied to identify factors associated with retweet frequency.

resultsAmong #vaccine tweets, provaccine tweets (adjusted prevalence ratio = 1.5836, 95% confidence interval = 1.2130-2.0713, p < 0.001) and antivaccine tweets (adjusted prevalence ratio = 4.1280, 95% confidence interval = 3.1183-5.4901, p < 0.001) had more retweets than neutral tweets. No significant differences occurred in retweet frequency for content categories among antivaccine tweets. Among 411 links in provaccine tweets, Twitter (53; 12.9%), content curator Trap.it (14; 3.4%), and the Centers for Disease Control and Prevention (8; 1.9%) ranked as the top 3 domains. Among 325 links in antivaccine tweets, social media links were common: Twitter (44; 14.9%), YouTube (25; 8.4%), and Facebook (10; 3.4%). Among highly retweeted #vaccineswork tweets, the most common theme was childhood vaccinations (40%; 81/201); 21% mentioned global vaccination improvement/efforts (42/201); 29% mentioned vaccines can prevent outbreaks and deaths (58/201).

conclusionEngaging social media key opinion leaders to facilitate health education about vaccination in their tweets may allow reaching a wider audience online.

Indexed as

Social MediaVaccinesChildHealth Knowledge, Attitudes, PracticeHumansVaccinationVaccines

Identifiers

PMID29911966
PMCPMC6004971

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.