CLAIMay 10, 2024

Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad

U of Toronto
arXiv:2405.06760v13 citationsh-index: 13
Originality Synthesis-oriented
AI Analysis

It addresses the need for computational methods in Persian literary studies, offering a case study for digital humanities research.

This study tackled the analysis of Persian poetry by applying AI language models to Forough Farrokhzad's work, resulting in the identification of thematic and stylistic patterns through unsupervised clustering.

This study explores the integration of advanced Natural Language Processing (NLP) and Artificial Intelligence (AI) techniques to analyze and interpret Persian literature, focusing on the poetry of Forough Farrokhzad. Utilizing computational methods, we aim to unveil thematic, stylistic, and linguistic patterns in Persian poetry. Specifically, the study employs AI models including transformer-based language models for clustering of the poems in an unsupervised framework. This research underscores the potential of AI in enhancing our understanding of Persian literary heritage, with Forough Farrokhzad's work providing a comprehensive case study. This approach not only contributes to the field of Persian Digital Humanities but also sets a precedent for future research in Persian literary studies using computational techniques.

Foundations

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