Evidence map›Paper›PMID 37616030›Full record

ArticleJournal of medical Internet research2023

Impact of Social Reference Cues on Misinformation Sharing on Social Media: Series of Experimental Studies.

Christopher M Jones, Daniel Diethei, Johannes Schöning, Rehana Shrestha, Tina Jahnel, Benjamin Schüz

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2023. 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
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. [Mis- and disinformation in social media: mitigating risks in digital health communication].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024
    Review
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

6 authors.

Christopher M JonesInstitute for Public Health and Nursing Research, University of Bremen, Bremen, Germany.ORCID 0000-0002-3182-8244
Daniel DietheiInstitute for Public Health and Nursing Research, University of Bremen, Bremen, Germany.ORCID 0000-0002-3435-5235
Johannes SchöningLeibniz ScienceCampus Digital Public Health, Bremen, Germany.ORCID 0000-0002-8823-4607
Rehana ShresthaInstitute for Public Health and Nursing Research, University of Bremen, Bremen, Germany.ORCID 0000-0001-9365-7375
Tina JahnelInstitute for Public Health and Nursing Research, University of Bremen, Bremen, Germany.ORCID 0000-0002-8367-4574
Benjamin SchüzInstitute for Public Health and Nursing Research, University of Bremen, Bremen, Germany.ORCID 0000-0002-0801-498X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth-related misinformation on social media is a key challenge to effective and timely public health responses. Existing mitigation measures include flagging misinformation or providing links to correct information, but they have not yet targeted social processes. Current approaches focus on increasing scrutiny, providing corrections to misinformation (debunking), or alerting users prospectively about future misinformation (prebunking and inoculation). Here, we provide a test of a complementary strategy that focuses on the social processes inherent in social media use, in particular, social reinforcement, social identity, and injunctive norms.

objectiveThis study aimed to examine whether providing balanced social reference cues (ie, cues that provide information on users sharing and, more importantly, not sharing specific content) in addition to flagging COVID-19-related misinformation leads to reductions in sharing behavior and improvement in overall sharing quality.

methodsA total of 3 field experiments were conducted on Twitter's native social media feed (via a newly developed browser extension). Participants' feed was augmented to include misleading and control information, resulting in 4 groups: no-information control, Twitter's own misinformation warning (misinformation flag), social cue only, and combined misinformation flag and social cue. We tracked the content shared or liked by participants. Participants were provided with social information by referencing either their personal network on Twitter or all Twitter users.

resultsA total of 1424 Twitter users participated in 3 studies (n=824, n=322, and n=278). Across all 3 studies, we found that social cues that reference users' personal network combined with a misinformation flag reduced the sharing of misleading but not control information and improved overall sharing quality. We show that this improvement could be driven by a change in injunctive social norms (study 2) but not social identity (study 3).

conclusionsSocial reference cues combined with misinformation flags can significantly and meaningfully reduce the amount of COVID-19-related misinformation shared and improve overall sharing quality. They are a feasible and scalable way to effectively curb the sharing of COVID-19-related misinformation on social media.

Indexed as

COVID-19Social MediaCommunicationCuesEmotionsHumansbehavior changeCOVID-19fake newsflaghealth literacyinfodemiologyinformation behaviorinformation sharingmisinformationsharing behaviorsocial cuesocial mediasocial referencetweetTwitter

Identifiers

PMID37616030
PMCPMC10485706

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.