Frequency in lexical processing. Issue 11 (1st November 2016)

• Record Type: Journal Article
• Authors: Baayen, R. Harald; Milin, Petar; Ramscar, Michael
• Is Part Of: Aphasiology. Volume 30:Issue 11(2016)
• Page Start: 1174
• Page End: 1220
• Publication Date: 2016-11-01
• Subjects: Lexical processing -- frequency -- age of acquisition -- naive discrimination learning -- activation -- prior availability -- subtitles; Aphasia -- Periodicals; Aphasia; 616.8552
• DOI: 10.1080/02687038.2016.1147767
• Languages: English
• ISSNs: 0268-7038

Abstract

ABSTRACT: Background : Frequency of occurrence is a strong predictor of lexical processing across modalities and experimental paradigms. However, frequency is part of a large set of collinear predictors including not only frequencies collected from different registers, but also a wide range of other lexical properties such as length, neighbourhood density, measures of valence, arousal, and dominance, semantic diversity, dispersion, age of acquisition, and measures grounded in discrimination learning. Aims : The aim of this study is to provide a critical examination of these variables, the sources on which they are based, the way they are calculated and evaluated, and their potential causal relations. Main Contribution : We show that age of acquisition ratings and subtitle frequencies constitute (reconstructed) genres that favour frequent use for very different subsets of words. As a consequence of the very different ways in which collinear variables profile as a function of genre, the fit between these variables and measures of lexical processing depends on both genre and task. A graphical model suggests that neither frequency nor age of acquisition are primary causal factors, but rather semantic and emotion measures as well as measures derived from discriminative learning. Conclusions : The methodological implication of these results is that when evaluating effects of lexical predictors on processing it is advisable to carefully consider what genres were used to obtain these predictors, and to consider the system of predictors and potential conditional independencies using graphical modelling.