Lingualyzer: A computational linguistic tool for multilingual and multidimensional text analysis.

Behav Res Methods

Department of Cognitive Science & Artificial Intelligence, Tilburg University, Tilburg, Netherlands.

Published: September 2024

AI Article Synopsis

  • Most natural language models primarily focus on English, limiting resources for researchers studying other languages.
  • There is a rising demand among interdisciplinary researchers for computational tools that can handle cross-linguistic comparisons, especially for those without strong programming skills.
  • Lingualyzer is introduced as an accessible tool that analyzes text across multiple levels and offers a wide range of linguistic measures in 41 languages, addressing this gap effectively.

Article Abstract

Most natural language models and tools are restricted to one language, typically English. For researchers in the behavioral sciences investigating languages other than English, and for those researchers who would like to make cross-linguistic comparisons, hardly any computational linguistic tools exist, particularly none for those researchers who lack deep computational linguistic knowledge or programming skills. Yet, for interdisciplinary researchers in a variety of fields, ranging from psycholinguistics, social psychology, cognitive psychology, education, to literary studies, there certainly is a need for such a cross-linguistic tool. In the current paper, we present Lingualyzer ( https://lingualyzer.com ), an easily accessible tool that analyzes text at three different text levels (sentence, paragraph, document), which includes 351 multidimensional linguistic measures that are available in 41 different languages. This paper gives an overview of Lingualyzer, categorizes its hundreds of measures, demonstrates how it distinguishes itself from other text quantification tools, explains how it can be used, and provides validations. Lingualyzer is freely accessible for scientific purposes using an intuitive and easy-to-use interface.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11335911PMC
http://dx.doi.org/10.3758/s13428-023-02284-1DOI Listing

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