Evidence map›Paper›PMID 36070451›Full record

ArticleJournal of medical Internet research2022

The Influence of Provaping "Gatewatchers" on the Dissemination of COVID-19 Misinformation on Twitter: Analysis of Twitter Discourse Regarding Nicotine and the COVID-19 Pandemic.

Nathan Silver, Elexis Kierstead, Ganna Kostygina, Hy Tran, Jodie Briggs, Sherry Emery, Barbara Schillo

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
4.7field-weighted citation impact, top 5% 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

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

7 authors at 2 institutions in 1 country.

Nathan SilverSchroeder Institute, Truth Initiative, Washington, DC, United States.ORCID 0000-0002-2889-4873
Elexis KiersteadSchroeder Institute, Truth Initiative, Washington, DC, United States.ORCID 0000-0002-8502-0451
Ganna KostyginaSocial Data Collaboratory, NORC at the University of Chicago, Chicago, IL, United States.ORCID 0000-0002-8416-6168
Hy TranSocial Data Collaboratory, NORC at the University of Chicago, Chicago, IL, United States.ORCID 0000-0001-6557-349X
Jodie BriggsSchroeder Institute, Truth Initiative, Washington, DC, United States.ORCID 0000-0002-9484-9050
Sherry EmerySocial Data Collaboratory, NORC at the University of Chicago, Chicago, IL, United States.ORCID 0000-0001-9278-9990
Barbara SchilloSchroeder Institute, Truth Initiative, Washington, DC, United States.ORCID 0000-0003-0847-2996
American Legacy Foundation · USUniversity of Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is a lot of misinformation about a potential protective role of nicotine against COVID-19 spread on Twitter despite significant evidence to the contrary. We need to examine the role of vape advocates in the dissemination of such information through the lens of the gatewatching framework, which posits that top users can amplify and exert a disproportionate influence over the dissemination of certain content through curating, sharing, or, in the case of Twitter, retweeting it, serving more as a vector for misinformation rather than the source.

objectiveThis research examines the Twitter discourse at the intersection of COVID-19 and tobacco (1) to identify the extent to which the most outspoken contributors to this conversation self-identify as vaping advocates and (2) to understand how and to what extent these vape advocates serve as gatewatchers through disseminating content about a therapeutic role of tobacco, nicotine, or vaping against COVID-19.

methodsTweets about tobacco, nicotine, or vaping and COVID-19 (N=1,420,271) posted during the first 9 months of the pandemic (January-September 2020) were identified from within a larger corpus of tobacco-related tweets using validated keyword filters. The top posters (ie, tweeters and retweeters) were identified and characterized, along with the most shared Uniform Resource Locators (URLs), most used hashtags, and the 1000 most retweeted posts. Finally, we examined the role of both top users and vape advocates in retweeting the most retweeted posts about the therapeutic role of nicotine, tobacco, or vaping against COVID-19.

resultsVape advocates comprised between 49.7% (n=81) of top 163 and 88% (n=22) of top 25 users discussing COVID-19 and tobacco on Twitter. Content about the ability of tobacco, nicotine, or vaping to treat or prevent COVID-19 was disseminated broadly, accounting for 22.5% (n=57) of the most shared URLs and 10% (n=107) of the most retweeted tweets. Finally, among top users, retweets comprised an average of 78.6% of the posts from vape advocates compared to 53.1% from others (z=3.34, P<.001). Vape advocates were also more likely to retweet the top tweeted posts about a therapeutic role of nicotine, with 63% (n=51) of vape advocates retweeting at least 1 post compared to 40.3% (n=29) of other top users (z=2.80, P=.01).

conclusionsProvaping users dominated discussions of tobacco use during the COVID-19 pandemic on Twitter and were instrumental in disseminating the most retweeted posts about a potential therapeutic role of tobacco use against the virus. Subsequent research is needed to better understand the extent of this influence and how to mitigate the influence of vape advocates over the broader narrative of tobacco regulation on Twitter.

Indexed as

COVID-19Social MediaCommunicationHumansNicotinePandemicsNicotineconsequencesCOVID-19environmentharmfulinfluenceinfodemiologyinformationmisinformationnicotinesocial mediatherapeutictobaccoTwittervaping

Identifiers

PMID36070451
PMCPMC9506503
OpenAlexW4293280604

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.