Predicting information credibility in time-sensitive social media
Open accessAbstract
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Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Castillo et al. (2013) found a 1:1 ratio of supporting to debunking tweets for false rumours in the 2010 Chile earthquake.
“Castillo et al. (2013) found that the ratio between tweets supporting and debunking false rumours was 1:1 (one supporting tweet per debunking tweet) in the case of a 2010 earthquake in Chile.”
From Detection and Resolution of Rumours in Social Media (2019) · cites this paper as Castillo et al. 2013
Approaches to mitigate the effects of misinformation and disinformation exist, including graph-based and text-based methods.
“Approaches to mitigate the effects of misinformation and disinformation exist, including graph-based (Ratkiewicz et al., 2011), and text-based (Castillo et al., 2013) methods.”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Castillo et al., 2013
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References 45 · Cited by 339
- Authors
- Castillo, C., Mendoza, M., & Poblete, B.
- Affiliations
- Universidad Técnica Federico Santa María (CL)
- Venue
- Internet Research
- Publisher
- Emerald
- Published
- 2013-10-14
- Volume
- 23
- Issue
- 5
- Pages
- 560-588
- ISSN
- 1066-2243 (ISSN-L)
- OpenAlex
- W1971494700
- Cited by
- 339
- References
- 45
- Citations by year
- 2026: 5 · 2025: 14 · 2024: 15 · 2023: 26 · 2022: 30 · 2021: 30 · 2020: 32 · 2019: 44 · 2018: 31 · 2017: 38 · 2016: 43 · 2015: 20 · 2014: 9 · 2013: 2
- FWCI
- 76.41
- Type
- journal article
- Language
- en
- Open access
- green
- americanae.aecid.es
- Licence
- Locations
- Internet Research (publishedVersion)
- Americanae (AECID Library) (submittedVersion, other-oa)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
- Universidad de Chile (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- information credibility, social media, misinformation
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.
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