Hello Aoir colleagues, My name is Bumju Jung (University of Southern California). Lynn Miller, Ph.D., and I are conducting a meta-analysis examining how deepfake videos, compared with authentic videos, shape credibility-related evaluations (e.g., perceived credibility, accuracy, authenticity, believability). First: Are we missing your study? If you have a study that matches the criteria below (published, in press, working paper, or unpublished), I would be grateful if you could contact me. This will help us ensure we do not miss your work and that we can accurately include and cite it in our meta-analysis. Unpublished and null findings are especially valuable for reducing publication bias. Second: If the paper or repository does not include complete statistics, it would be incredibly helpful to receive the minimum information needed to compute effect sizes, ideally: * Sample size per condition (deepfake/synthetic vs. authentic; N per cell) * Means and SDs for relevant outcomes (or equivalent statistics: t/F, SE, CI, etc.) When you do not need to send anything: If all necessary statistics are already available in the paper, appendix, OSF, or another repository, you do not need to forward numbers. A link or citation is enough (so we do not miss it). High-level inclusion criteria: * Experimental or quasi-experimental design * Video stimuli: deepfake/AI synthesized vs. authentic video comparison * Measures: perceived credibility/accuracy/authenticity/believability (or closely related outcomes) Please email me at bumjujun@usc.edu<mailto:bumjujun@usc.edu> Many thanks! Bumju Jung (he/him/his) Annenberg School for Communication and Journalism University of Southern California