A State-of-the-Art of Semantic Change Computation

TL;DR

This paper reviews the current methods for analyzing semantic change over time, highlighting key components, challenges, and future directions in computational linguistics research.

Contribution

It proposes a comprehensive framework for semantic change computation, summarizing existing literature and identifying core issues and gaps in the field.

Findings

Most studies focus on testing linguistic hypotheses.

Limited diachronic corpora for languages other than English.

Need for standardized evaluation data and advanced visualization techniques.

Abstract

This paper reviews the state-of-the-art of semantic change computation, one emerging research field in computational linguistics, proposing a framework that summarizes the literature by identifying and expounding five essential components in the field: diachronic corpus, diachronic word sense characterization, change modelling, evaluation data and data visualization. Despite the potential of the field, the review shows that current studies are mainly focused on testifying hypotheses proposed in theoretical linguistics and that several core issues remain to be solved: the need for diachronic corpora of languages other than English, the need for comprehensive evaluation data for evaluation, the comparison and construction of approaches to diachronic word sense characterization and change modelling, and further exploration of data visualization techniques for hypothesis justification.