# Modeling Language Change in Historical Corpora: The Case of Portuguese

arXiv: https://arxiv.org/abs/1610.00030 · HTML: https://mlsanity.com/paper/1610.00030/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Sep 2016.

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

- [Lexical semantic change for Ancient Greek and Latin](https://mlsanity.com/paper/2101.09069/) (2021)
- [Exploring Diachronic and Diatopic Changes in Dialect Continua: Tasks, Datasets and Challenges](https://mlsanity.com/paper/2407.04010/) (2024)
- [Temporal Text Classification with Large Language Models](https://mlsanity.com/paper/2603.11295/) (2026)

## Abstract (arXiv)

This paper presents a number of experiments to model changes in a historical Portuguese corpus composed of literary texts for the purpose of temporal text classification. Algorithms were trained to classify texts with respect to their publication date taking into account lexical variation represented as word n-grams, and morphosyntactic variation represented by part-of-speech (POS) distribution. We report results of 99.8% accuracy using word unigram features with a Support Vector Machines classifier to predict the publication date of documents in time intervals of both one century and half a century. A feature analysis is performed to investigate the most informative features for this task and how they are linked to language change.