# TextDescriptives: A Python package for calculating a large variety of metrics from text

arXiv: https://arxiv.org/abs/2301.02057 · HTML: https://mlsanity.com/paper/2301.02057/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 15 references that are in the map.
- First posted on arXiv 5 Jan 2023.

## Builds on (most cited first, 2 of 2)

- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [Scaling Language Models: Methods, Analysis & Insights from Training Gopher](https://mlsanity.com/paper/2112.11446/) (2021)

## Built on by (most cited first, 13 of 13)

- [Beemo: Benchmark of Expert-edited Machine-generated Outputs](https://mlsanity.com/paper/2411.04032/) (2024)
- [A Novel Approach to Scalable and Automatic Topic-Controlled Question Generation in Education](https://mlsanity.com/paper/2501.05220/) (2025)
- [Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual Progress](https://mlsanity.com/paper/2408.14960/) (2024)
- [Alignment Drift in CEFR-prompted LLMs for Interactive Spanish Tutoring](https://mlsanity.com/paper/2505.08351/) (2025)
- [LLM See, LLM Do: Guiding Data Generation to Target Non-Differentiable Objectives](https://mlsanity.com/paper/2407.01490/) (2024)
- [Statistical Depth for Ranking and Characterizing Transformer-Based Text Embeddings](https://mlsanity.com/paper/2310.15010/) (2023)
- [MAiDE-up: Multilingual Deception Detection of GPT-generated Hotel Reviews](https://mlsanity.com/paper/2404.12938/) (2024)
- [A Lightweight Approach to Detection of AI-Generated Texts Using Stylometric Features](https://mlsanity.com/paper/2511.21744/) (2025)
- [DACTYL: Diverse Adversarial Corpus of Texts Yielded from Large Language Models](https://mlsanity.com/paper/2508.00619/) (2025)
- [Which LLMs are Difficult to Detect? A Detailed Analysis of Potential Factors Contributing to Difficulties in LLM Text Detection](https://mlsanity.com/paper/2410.14875/) (2024)
- [Facilitating Cognitive Accessibility with LLMs: A Multi-Task Approach to Easy-to-Read Text Generation](https://mlsanity.com/paper/2510.00662/) (2025)
- [Mining Reasons For And Against Vaccination From Unstructured Data Using Nichesourcing and AI Data Augmentation](https://mlsanity.com/paper/2406.19951/) (2024)
- [Bias Dynamics in BabyLMs: Towards a Compute-Efficient Sandbox for Democratising Pre-Training Debiasing](https://mlsanity.com/paper/2601.09421/) (2026)

## Abstract (arXiv)

TextDescriptives is a Python package for calculating a large variety of metrics from text. It is built on top of spaCy and can be easily integrated into existing workflows. The package has already been used for analysing the linguistic stability of clinical texts, creating features for predicting neuropsychiatric conditions, and analysing linguistic goals of primary school students. This paper describes the package and its features.