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

arXiv: https://arxiv.org/abs/2405.06760 · HTML: https://mlsanity.com/paper/2405.06760/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 43 references that are in the map.
- First posted on arXiv 10 May 2024.

## Builds on (most cited first, 6 of 6)

- [UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction](https://mlsanity.com/paper/1802.03426/) (2018)
- [ParsBERT: Transformer-based Model for Persian Language Understanding](https://mlsanity.com/paper/2005.12515/) (2020)
- [Prose2Poem: The Blessing of Transformers in Translating Prose to Persian Poetry](https://mlsanity.com/paper/2109.14934/) (2021)
- [Creating a New Persian Poet Based on Machine Learning](https://mlsanity.com/paper/1810.06898/) (2018)
- [Sentiment Dynamics of Success: Fractal Scaling of Story Arcs Predicts Reader Preferences](https://mlsanity.com/paper/2112.07497/) (2021)
- [KhabarChin: Automatic Detection of Important News in the Persian Language](https://mlsanity.com/paper/2312.03361/) (2023)

## Built on by (most cited first, 3 of 3)

- [NAZM: Network Analysis of Zonal Metrics in Persian Poetic Tradition](https://mlsanity.com/paper/2505.08052/) (2025)
- [A Dynamic Atlas of Persian Poetic Symbolism: Families, Fields, and the Historical Rewiring of Meaning](https://mlsanity.com/paper/2604.01467/) (2026)
- [Echoes Across Centuries: Phonetic Signatures of Persian Poets](https://mlsanity.com/paper/2603.14443/) (2026)

## Abstract (arXiv)

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.