Towards cognitively plausible data science in language research

Petar Milin, Dagmar Divjak, Strahinja Dimitrijević, R. Harald Baayen

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)
155 Downloads (Pure)

Abstract

Over the past 10 years, Cognitive Linguistics has taken a quantitative turn. Yet, concerns have been raised that this preoccupation with quantification and modelling may not bring us any closer to understanding how language works. We show that this objection is unfounded, especially if we rely on modelling techniques based on biologically and psychologically plausible learning algorithms. These make it possible to take a quantitative approach, while generating and testing specific hypotheses that will advance our understanding of how knowledge of language emerges from exposure to usage.
Original languageEnglish
Pages (from-to)507-526
Number of pages20
JournalCognitive Linguistics
Volume27
Issue number4
Early online date7 Oct 2016
DOIs
Publication statusPublished - 1 Nov 2016

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