Computational modeling of semantic change

TL;DR

This paper reviews computational methods for modeling semantic change using large textual corpora, discussing their interpretation, evaluation, and suitability for different data types.

Contribution

It provides a comprehensive overview of modeling techniques, evaluation methods, and key considerations for studying semantic change computationally.

Findings

Different classes of models have specific strengths and limitations.

Evaluation techniques are crucial for assessing model performance.

Insights into data properties influence model choice and interpretation.

Abstract

In this chapter we provide an overview of computational modeling for semantic change using large and semi-large textual corpora. We aim to provide a key for the interpretation of relevant methods and evaluation techniques, and also provide insights into important aspects of the computational study of semantic change. We discuss the pros and cons of different classes of models with respect to the properties of the data from which one wishes to model semantic change, and which avenues are available to evaluate the results.