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

TL;DR

This paper demonstrates how AI and NLP techniques, especially transformer models, can analyze Persian poetry, revealing thematic and stylistic patterns, and advancing Persian Digital Humanities research through computational methods.

Contribution

It introduces a novel application of transformer-based AI models to analyze Persian literature, specifically the poetry of Forough Farrokhzad, in an unsupervised framework.

Findings

Unveiled thematic and stylistic patterns in Farrokhzad's poetry.

Showed AI's potential to enhance understanding of Persian literary heritage.

Established a computational approach for future Persian literary studies.

Abstract

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.