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20212026
most citedForegrounding Artist Opinions: A Survey Study on Transparency, Ownership, and Fairness in AI Generative Art

3 citations · 8 across the 14 of their papers we have counts for

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cs.CY2026

The queer Hero versus the Fool bias of the queer trait: An archetypometric analysis of the collective portrayal of queerness in fictional stories

Ashley M. A. Fehr, Calla Glavin Beauregard, Julia Witte Zimmerman +4

Visibility in media is pivotal for identity development and for broadening societal views of gender and sexuality. Queer representation has increased in recent years, yet damaging…

cs.CY2026

Buffy versus Bella: An archetypometric analysis and comparison

Calla Glavin Beauregard, Julia Witte Zimmerman, Ashley M. A. Fehr +6

Fictional stories and characters embody and encode social norms, and their study is a powerful tool through which to understand culture and society. Vampire stories and folklore, i…

cs.CY2026

Archetypes and gender in fiction: A data-driven mapping of gender stereotypes in stories

Calla Glavin Beauregard, Julia Witte Zimmerman, Ashley M. A. Fehr +3

Fictional character representations reflect social norms and biases. For example, women are relatively underrepresented in television and film, irrespective of genre, and are frequ…

cs.CY2025

Us-vs-Them bias in Large Language Models

Tabia Tanzin Prama, Julia Witte Zimmerman, Christopher M. Danforth +1

This study investigates ``us versus them'' bias, as described by Social Identity Theory, in large language models (LLMs) under both default and persona-conditioned settings across…

cs.CY2024★ 3 cited

Foregrounding Artist Opinions: A Survey Study on Transparency, Ownership, and Fairness in AI Generative Art

Juniper Lovato, Julia Zimmerman, Isabelle Smith +2

Generative AI tools are used to create art-like outputs and sometimes aid in the creative process. These tools have potential benefits for artists, but they also have the potential…