Cited by 3Misinformation and Its ImpactsLibrary Science and Information LiteracyHealth Literacy and Information Accessibility

Multidimensional Information Literacy and Fact-Checking Behavior: A Person-Centered Approach Using Latent Profile Analysis

Shen, Xiao-Liang, Wu, You·2024·Lecture Notes in Computer Science

Integrity signals

Registry

Crossref · 10.1007/978-3-031-57860-1_20

Cites

17 of 17 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

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Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Latent class analysis expands analytical possibilities by moving beyond predefined groups to reveal hidden subpopulations whose vulnerabilities stem from unique combinations of beliefs, emotional traits, and media engagement patterns.

    “Latent class analysis (LCA) expands analytical possibilities by moving beyond predefined groups to reveal hidden subpopulations whose vulnerabilities stem from unique combinations of beliefs, emotional traits, and media engagement patterns (Shen & Wu, 2024).”

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Authors
Shen, X.-L., & Wu, Y.
Affiliations
Wuhan University (CN)
Corresponding author
Shen, Xiao-Liang
Venue
Lecture Notes in Computer Science
Published
2024
Pages
280-297
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W4394626763
Cited by
2
References
17
Citations by year
2026: 1 · 2025: 1
FWCI
2.62
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Social Sciences › Library and Information Sciences › Library Science and Information Literacy
  • Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
Keywords
information literacy, social media users, misinformation, rumor propagation, user profiles, latent profiles, person-centered approach

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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