Spelling performance on the web and in the lab


Autoři: Arnaud Rey aff001;  Jean-Luc Manguin aff003;  Chloé Olivier aff001;  Sébastien Pacton aff004;  Pierre Courrieu aff001
Působiště autorů: Laboratoire de Psychologie Cognitive, CNRS—Aix-Marseille Université, Marseille, France aff001;  Institute of Language, Communication and the Brain, Aix-Marseille Université, Marseille, France aff002;  GREYC, CNRS—Université de Caen Basse-Normandie–ENSICAEN, Caen, France aff003;  Laboratoire Mémoire, Cerveau et Cognition, Université Paris Descartes, Paris, France aff004
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226647

Souhrn

Several dictionary websites are available on the web to access semantic, synonymous, or spelling information about a given word. During nine years, we systematically recorded all the entered letter sequences from a French web dictionary. A total of 200 million orthographic forms were obtained allowing us to create a large-scale database of spelling errors that could inform psychological theories about spelling processes. To check the reliability of this big data methodology, we selected from this database a sample of 100 frequently misspelled words. A group of 100 French university students had to perform a spelling-to-dictation test on this list of words. The results showed a strong correlation between the two data sets on the frequencies of produced spellings (r = 0.82). Although the distributions of spelling errors were relatively consistent across the two databases, the proportion of correct responses revealed significant differences. Regression analyses allowed us to generate possible explanations for these differences in terms of task-dependent factors. We argue that comparing the results of these large-scale databases with those of standard and controlled experimental paradigms is certainly a good way to determine the conditions under which this big data methodology can be adequately used for informing psychological theories.

Klíčová slova:

Database and informatics methods – Experimental psychology – Information retrieval – Lexicons – Phonemes – Phonology – Regression analysis – Semantics


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Článek vyšel v časopise

PLOS One


2019 Číslo 12