Evidence map›Paper›PMID 35128039›Full record

ArticleInternational journal of data science and analytics2022

Beyond belief: a cross-genre study on perception and validation of health information online.

Chaoyuan Zuo, Kritik Mathur, Dhruv Kela, Noushin Salek Faramarzi, Ritwik Banerjee

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of data science and analytics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Online information disorder: fake news, bots and trolls.International journal of data science and analytics · 2022
    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

5 authors.

Chaoyuan ZuoStony Brook University, Stony Brook, NY 11794-2424 USA.ORCID 0000-0001-5361-0193
Kritik MathurStony Brook University, Stony Brook, NY 11794-2424 USA.
Dhruv KelaStony Brook University, Stony Brook, NY 11794-2424 USA.
Noushin Salek FaramarziStony Brook University, Stony Brook, NY 11794-2424 USA.
Ritwik BanerjeeStony Brook University, Stony Brook, NY 11794-2424 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural language undergoes significant transformation from the domain of specialized research to general news intended for wider consumption. This transition makes the information vulnerable to misinterpretation, misrepresentation, and incorrect attribution, all of which may be difficult to identify without adequate domain knowledge and may exist even in the presence of explicit citations. Moreover, newswire articles seldom provide a precise correspondence between a specific claim and its origin, making it harder to identify

Indexed as

Check-worthinessClaim extractionCross-genre information retrievalFact-checkingMisinformationNatural language processing

Identifiers

PMID35128039
PMCPMC8807956

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.