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Word maturity indices with latent semantic analysis: why, when, and where is Procrustes rotation applied?
Author(s) -
JorgeBotana Guillermo,
Olmos Ricardo,
Luzón José M.
Publication year - 2017
Publication title -
wiley interdisciplinary reviews: cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.526
H-Index - 49
eISSN - 1939-5086
pISSN - 1939-5078
DOI - 10.1002/wcs.1457
Subject(s) - computer science , latent semantic analysis , word (group theory) , natural language processing , representation (politics) , meaning (existential) , artificial intelligence , simple (philosophy) , linguistics , computational linguistics , word association , psychology , philosophy , epistemology , politics , political science , law , psychotherapist
The aim of this paper is to describe and explain one useful computational methodology to model the semantic development of word representation: Word maturity. In particular, the methodology is based on the longitudinal word monitoring created by Kirylev and Landauer using latent semantic analysis for the representation of lexical units. The paper is divided into two parts. First, the steps required to model the development of the meaning of words are explained in detail. We describe the technical and theoretical aspects of each step. Second, we provide a simple example of application of this methodology with some simple tools that can be used by applied researchers. This paper can serve as a user‐friendly guide for researchers interested in modeling changes in the semantic representations of words. Some current aspects of the technique and future directions are also discussed. WIREs Cogn Sci 2018, 9:e1457. doi: 10.1002/wcs.1457 This article is categorized under: Computer Science > Natural Language Processing Linguistics > Language Acquisition Psychology > Development and Aging