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Cognitive Science
Article . 2021 . Peer-reviewed
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Cognitive Science
Article
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https://doi.org/10.31234/osf.i...
Article . 2020 . Peer-reviewed
License: CC BY
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DBLP
Article . 2021
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Modeling Misretrieval and Feature Substitution in Agreement Attraction: A Computational Evaluation

Authors: Dario Paape; Serine Avetisyan; Sol Lago; Shravan Vasishth;

Modeling Misretrieval and Feature Substitution in Agreement Attraction: A Computational Evaluation

Abstract

Abstract We present computational modeling results based on a self‐paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k‐fold cross‐validation. We find that our data are better accounted for by an encoding‐based model of agreement attraction, compared to a retrieval‐based model. A novel methodological contribution of our study is the use of comprehension questions with open‐ended responses, so that both misinterpretation of the number feature of the subject phrase and misassignment of the thematic subject role of the verb can be investigated at the same time. We find evidence for both types of misinterpretation in our study, sometimes in the same trial. However, the specific error patterns in our data are not fully consistent with any previously proposed model.

Country
Germany
Keywords

ddc:400, Reading, ddc:410, 150, Humans, Bayes Theorem, Comprehension, 410, 400, Language

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    22
    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Top 10%
Average
Top 10%
Green
hybrid