Word Sense Detection Leveraging Maximum Mean Discrepancy

TL;DR

This paper introduces MMD-Sense-Analysis, a novel method using Maximum Mean Discrepancy to detect and interpret word sense changes over time, providing a new tool for linguistic and social analysis.

Contribution

It is the first application of MMD to word sense change detection, enabling identification and explanation of sense shifts across historical periods.

Findings

Effective detection of word sense shifts over time

First use of MMD in this domain

Demonstrated superior performance empirically

Abstract

Word sense analysis is an essential analysis work for interpreting the linguistic and social backgrounds. The word sense change detection is a task of identifying and interpreting shifts in word meanings over time. This paper proposes MMD-Sense-Analysis, a novel approach that leverages Maximum Mean Discrepancy (MMD) to select semantically meaningful variables and quantify changes across time periods. This method enables both the identification of words undergoing sense shifts and the explanation of their evolution over multiple historical periods. To my knowledge, this is the first application of MMD to word sense change detection. Empirical assessment results demonstrate the effectiveness of the proposed approach.