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== Considered variables == | == Considered variables == | ||
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* '''Semantically related (vs not related)''' | * '''Semantically related (vs not related)''' | ||
* Type of sentences '''Simple / hard''' ([[Nonprobative photographs (or words) inflate truthiness|Newmann, et al., 2012]]) | * Type of sentences '''Simple / hard''' ([[Nonprobative photographs (or words) inflate truthiness|Newmann, et al., 2012]]) | ||
Version du 25 novembre 2025 à 21:36
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
Related to images
- 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 :
- Obviously AI generated (vs "real") : Les gens rapportent avoir une bonne capacité à distinguer une image IA d'une image réelle, mais les études sur le domaine montre que ce n'est pas le cas (Nightingale & Harid, 2021 in Newman & Schwarz, 2024)
- 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)
- Visual formats & features (Peng, Lu & Shen, 2023)
- Formats
- photo (Picture (vs drawing))
- video
- meme
- data visualization
- Objective features
- color (simple values like brightness and saturation can be directly extracted from the colorspace, and these features were found to affect attention (Camgöz et al., 2004), visual working memory (Qian et al., 2018), and the viewer’s sense of pleasure (Lichtlé, 2007). Different colors may be associated with various human affect and behaviors, with warm colors associated with more positive feelings than cool colors (Bakhshi et al., 2015; Peng & Jemmott, 2018).)
- composition
- people & objects
- video features
- Percieved features
- professional quality
- aestehetic appeal
- percieved realism
- vividness
- sentiment
- impression
- Formats
- Usage des images (Peng, Lu & Shen, 2023)
- visual features as arguments
- visual features as heuristics
- visual features as attention determinants
Related to subject
- Conspiracy Theory related (vs not related)
- Semantically related (vs not related)
- Type of sentences Simple / hard (Newmann, et al., 2012)