Fairy Tale

Fairy tales, as a rich source of cultural narratives, are increasingly being analyzed using computational methods to uncover underlying biases and values. Current research employs natural language processing techniques, including word embeddings and large language models (LLMs), to quantify gender stereotypes, moral frameworks, and cross-cultural variations in value representation within these stories. This work reveals significant gender imbalances and stereotypical portrayals, highlighting the potential for computational analysis to inform both literary studies and the development of less biased children's literature. Furthermore, the application of LLMs to summarize and analyze these lengthy texts presents challenges and opportunities for advancing long-context understanding in AI.