The Face of Persuasion: Analyzing Bias and Generating Culture-Aware Ads
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866912653974175744 |
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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 |