The Face of Persuasion: Analyzing Bias and Generating Culture-Aware Ads

Fuente: arXiv
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Autori principali: Aghazadeh, Aysan, Kovashka, Adriana
Natura: Preprint
Pubblicazione: 2025
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author Aghazadeh, Aysan
Kovashka, Adriana
author_facet Aghazadeh, Aysan
Kovashka, Adriana
contents Text-to-image models are appealing for customizing visual advertisements and targeting specific populations. We investigate this potential by examining the demographic bias within ads for different ad topics, and the disparate level of persuasiveness (judged by models) of ads that are identical except for gender/race of the people portrayed. We also experiment with a technique to target ads for specific countries. The code is available at https://github.com/aysanaghazadeh/FaceOfPersuasion
format Preprint
id arxiv_https___arxiv_org_abs_2510_15240
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Face of Persuasion: Analyzing Bias and Generating Culture-Aware Ads
Aghazadeh, Aysan
Kovashka, Adriana
Computer Vision and Pattern Recognition
Text-to-image models are appealing for customizing visual advertisements and targeting specific populations. We investigate this potential by examining the demographic bias within ads for different ad topics, and the disparate level of persuasiveness (judged by models) of ads that are identical except for gender/race of the people portrayed. We also experiment with a technique to target ads for specific countries. The code is available at https://github.com/aysanaghazadeh/FaceOfPersuasion
title The Face of Persuasion: Analyzing Bias and Generating Culture-Aware Ads
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2510.15240