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A Personal Model of Trumpery: Linguistic Deception Detection in a Real-World High-Stakes Setting
- Source :
- Psychological Science, 33(1), 3. SAGE Publications Inc., Psychological Science, 33(1), 3-17. SAGE Publishing, Psychological Science, Psychological Science, 2022, 33 (1), pp.3-17. ⟨10.1177/09567976211015941⟩
- Publication Year :
- 2021
-
Abstract
- International audience; Language use differs between truthful and deceptive statements, but not all differences are consistent across people and contexts, complicating the identification of deceit in individuals. By relying on fact-checked tweets, we showed in three studies (Study 1: 469 tweets; Study 2: 484 tweets; Study 3: 24 models) how well personalized linguistic deception detection performs by developing the first deception model tailored to an individual: the 45th U.S. president. First, we found substantial linguistic differences between factually correct and factually incorrect tweets. We developed a quantitative model and achieved 73% overall accuracy. Second, we tested out-of-sample prediction and achieved 74% overall accuracy. Third, we compared our personalized model with linguistic models previously reported in the literature. Our model outperformed existing models by 5 percentage points, demonstrating the added value of personalized linguistic analysis in real-world settings. Our results indicate that factually incorrect tweets by the U.S. president are not random mistakes of the sender.
- Subjects :
- Deception
05 social sciences
Twitter
LIWC
[SHS.PSY]Humanities and Social Sciences/Psychology
open data
050109 social psychology
Linguistics
deception detection
050105 experimental psychology
open materials
[SHS]Humanities and Social Sciences
tailored model
Humans
0501 psychology and cognitive sciences
Psychology(all)
General Psychology
linguistic analysis
Subjects
Details
- ISSN :
- 14679280 and 09567976
- Volume :
- 33
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Psychological science
- Accession number :
- edsair.doi.dedup.....9ebee5cbaff045c09ddfd6524bc916bc