# An Introduction to a New Text Classification and Visualization for Natural Language Processing Using Topological Data Analysis

arXiv: https://arxiv.org/abs/1906.01726 · HTML: https://mlsanity.com/paper/1906.01726/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jun 2019.

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

- [AI-generated text boundary detection with RoFT](https://mlsanity.com/paper/2311.08349/) (2023)
- [Topological Perspectives on Optimal Multimodal Embedding Spaces](https://mlsanity.com/paper/2405.18867/) (2024)
- [Topological Data Analysis Applications in Natural Language Processing: A Survey](https://mlsanity.com/paper/2411.10298/) (2024)

## Abstract (arXiv)

Topological Data Analysis (TDA) is a novel new and fast growing field of data science providing a set of new topological and geometric tools to derive relevant features out of complex high-dimensional data. In this paper we apply two of best methods in topological data analysis, "Persistent Homology" and "Mapper", in order to classify persian poems which has been composed by two of the best Iranian poets namely "Ferdowsi" and "Hafez". This article has two main parts, in the first part we explain the mathematics behind these two methods which is easy to understand for general audience and in the second part we describe our models and the results of applying TDA tools to NLP.