Detecting Turkish Synonyms Used in Different Time Periods

TL;DR

This paper introduces two novel methods for detecting Turkish synonyms across different historical periods by aligning word embeddings and incorporating frequency correlations, addressing language evolution challenges in NLP.

Contribution

It proposes two new approaches for identifying synonyms in Turkish over time, improving upon baseline methods by using embedding alignment and frequency analysis.

Findings

Proposed methods outperform baseline in synonym detection.

Method efficacy remains stable from 1960s to 1980s.

Performance slightly declines for later periods.

Abstract

Dynamic structure of languages poses significant challenges in applying natural language processing models on historical texts, causing decreased performance in various downstream tasks. Turkish is a prominent example of rapid linguistic transformation due to the language reform in the 20th century. In this paper, we propose two methods for detecting synonyms used in different time periods, focusing on Turkish. In our first method, we use Orthogonal Procrustes method to align the embedding spaces created using documents written in the corresponding time periods. In our second method, we extend the first one by incorporating Spearman's correlation between frequencies of words throughout the years. In our experiments, we show that our proposed methods outperform the baseline method. Furthermore, we observe that the efficacy of our methods remains consistent when the target time period shifts from the 1960s to the 1980s. However, their performance slightly decreases for subsequent time periods.