« Ébauche de première étude » : différence entre les versions
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* Behavioral | * Behavioral | ||
** C scores ([[Nonprobative photographs (or words) inflate truthiness|Newman et al., 2012]]) | ** '''C scores''' ([[Nonprobative photographs (or words) inflate truthiness|Newman et al., 2012]]) | ||
** Proportion of "true" ([[Evidence that photos promote rosiness for claims about the future|Newman et al., 2018]]) | ** '''Proportion of "true"''' ([[Evidence that photos promote rosiness for claims about the future|Newman et al., 2018]]) | ||
** Likert scale | ** '''Likert scale: Croyance dans la headline (0-10)''' ([[Properties of AI-generated images that influence misinformation belief and correction efficacy|Guo, S., Zhong & Hu, 2024]]) | ||
* Physiological | * Physiological | ||
** Eye-tracking | ** Eye-tracking | ||
=== Independant variables === | === Independant variables === | ||
Version du 25 novembre 2025 à 07:43
General idea
The main goal of this research will be to partially reproduce the design proposed by Newman & colleagues (2012; 2018; 2020) used to test the Truthiness effect which is testing how images influence perceptions of truth (cf Newman & Schwarz, 2024).
Introduction
Semantically related contexts produce easier conceptual processing relative to neutral contexts, an experience that people may interpret as evidence of familiarity. Likewise, semantically priming, repeating, or retrieving related information can produce illusions of frequency, familiarity, and truth—presumably due to increased ease of retrieval or cognitive availabilit (Newman et al., 2015)
Example of Stimuli
Considered variables
Dependant variables
- Behavioral
- C scores (Newman et al., 2012)
- Proportion of "true" (Newman et al., 2018)
- Likert scale: Croyance dans la headline (0-10) (Guo, S., Zhong & Hu, 2024)
- Physiological
- Eye-tracking
Independant variables
- Image/no image : no photo items serve as a benchmark for processing by manipulating the presence of photos within and between-subjects. If the effect of photos depends on a comparison against a (no photo) standard, we should expect to see the most pronounced effects of photos in our within-subject designs (Newman et al., 2015)
- Type of image :
- Semantically related (vs semantically not related)
- Obviously AI generated (vs "real")
- Conspiracy Theory related (vs not related)
- Picture (vs drawing)
- Image quality : perceptual fluency and manipulations such as degraded images, difficult fonts, and low contrast colors that require people to invest more cognitive effort to make sense of stimuli, which in turn can bias people toward evaluating these stimuli more negatively the context of a truth judgment, additional cognitive effort might be taken as a signal that the information being evaluated is false. (Newman et al., 2015)
- Type of sentences relatde
- Simple / hard (Newmann, et al., 2012)