Evidence map›Paper›PMID 35974879›Full record

ArticleComputers in human behavior2023

What message features influence the intention to share misinformation about COVID-19 on social media? The role of efficacy and novelty.

Hayeon Song, Jiyeon So, Minsun Shim, Jieun Kim, Eunji Kim, Kyungha Lee

Abstract read
In one paragraph

Article in Computers in human behavior, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. 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

6 authors.

Hayeon SongDepartment of Human-AI Interaction, Sungkyunkwan University, Seoul, South Korea.
Jiyeon SoDepartment of Communication, Yonsei University, Seoul, South Korea.
Minsun ShimDepartment of Media and Communication, Inha University, Incheon, South Korea.
Jieun KimDepartment of Information Science, Cornell University, Ithaca NY, USA.
Eunji KimDepartment of Human-AI Interaction, Sungkyunkwan University, Seoul, South Korea.
Kyungha LeeDepartment of Human-AI Interaction, Sungkyunkwan University, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the amount of misinformation being circulated on social media during the COVID-19 pandemic and its potential threat to public health, it is imperative to investigate ways to hinder its transmission. To this end, this study aimed to identify message features that may contribute to misinformation sharing on social media. Based on the theory of social sharing of emotion and the extant research on message credibility, this study examined if emotions and message credibility serve as mechanisms through which novelty and efficacy of misinformation influence sharing intention. An online experiment concerning COVID-19 misinformation was conducted by employing a 2 (novelty conditions: high vs. low) × 2 (efficacy conditions: high vs. low) between-subjects design using a national quota sample in South Korea (

Indexed as

COVID-19EfficacyEmotionFake newsMessage credibilityMisinformationNoveltySharing intention

Identifiers

PMID35974879
PMCPMC9371473

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.