Multilingual textual data: an approach through multiple factor analysis

TL;DR

This paper introduces MFA-GALT, a novel method for analyzing multilingual open-ended survey responses by examining relationships between word choices and contextual variables across different languages and samples.

Contribution

The paper presents MFA-GALT, a new analytical approach for jointly studying multilingual textual data and their associated contextual variables.

Findings

MFA-GALT effectively reveals structured variability in multilingual responses.

The method provides easy-to-interpret results in international survey analysis.

Application demonstrates the approach's utility in real-world multilingual data.

Abstract

This paper focuses on the analysis of open-ended questions answered in different languages. Closed-ended questions, called contextual variables, are asked to all respondents in order to understand the relationships between the free and the closed responses among the different samples since the latter assumably affect the word choices. We have developed "Multiple Factor Analysis on Generalized Aggregated Lexical Tables" (MFA-GALT) to jointly study the open-ended responses in different languages through the relationships between the choice of words and the variables that drive this choice. MFA-GALT studies if variability among words is structured in the same way by variability among variables, and inversely, from one sample to another. An application on an international satisfaction survey shows the easy-to-interpret results that are proposed.