Evidence map›Paper›PMID 39430219›Full record

ArticlePNAS nexus2024

Collaboration, crowdsourcing, and misinformation.

Chenyan Jia, Angela Yuson Lee, Ryan C Moore, Cid Halsey-Steve Decatur, Sunny Xun Liu, Jeffrey T Hancock

Abstract read
In one paragraph

Article in PNAS nexus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Chenyan JiaCollege of Arts, Media and Design and Khoury College of Computer Sciences, Northeastern University, Boston, MA 02115, USA.ORCID https://orcid.org/0000-0002-8407-9224
Angela Yuson LeeDepartment of Communication, Stanford University, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0002-9527-5730
Ryan C MooreDepartment of Communication, Stanford University, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0002-5669-721X
Cid Halsey-Steve DecaturDepartment of Communication, Stanford University, Stanford, CA 94305, USA.ORCID https://orcid.org/0009-0006-8403-6546
Sunny Xun LiuDepartment of Communication, Stanford University, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0001-8910-9384
Jeffrey T HancockDepartment of Communication, Stanford University, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0001-5367-2677

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of humanity's greatest strengths lies in our ability to collaborate to achieve more than we can alone. Just as collaboration can be an important strength, humankind's inability to detect deception is one of our greatest weaknesses. Recently, our struggles with deception detection have been the subject of scholarly and public attention with the rise and spread of misinformation online, which threatens public health and civic society. Fortunately, prior work indicates that going beyond the individual can ameliorate weaknesses in deception detection by promoting active discussion or by harnessing the "wisdom of crowds." Can group collaboration similarly enhance our ability to recognize online misinformation? We conducted a lab experiment where participants assessed the veracity of credible news and misinformation on social media either as an actively collaborating group or while working alone. Our results suggest that collaborative groups were more accurate than individuals at detecting false posts, but not more accurate than a majority-based simulated group, suggesting that "wisdom of crowds" is the more efficient method for identifying misinformation. Our findings reorient research and policy from focusing on the individual to approaches that rely on crowdsourcing or potentially on collaboration in addressing the problem of misinformation.

Indexed as

collaborationgroup discussionlab experimentmisinformationsocial media

Identifiers

PMID39430219
PMCPMC11488513

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.