Replication Data for: Exposure and Emergence in Usage-Based Grammar: Computational Experiments in 35 Languageshttps://doi.org/10.18710/CES0L8Dunn, JonathanDataverseNO2022-11-222023-09-28T19:53:53Z<p> <i>[article abstract:] </i> This paper uses computational experiments to explore the role of exposure in the emergence of construction grammars. While usage-based grammars are hypothesized to depend on a learner’s exposure to actual language use, the mechanisms of such exposure have only been studied in a few constructions in isolation. This paper experiments with (i) the growth rate of the constructicon, (ii) the convergence rate of grammars exposed to independent registers, and (iii) the rate at which constructions are forgotten when they have not been recently observed. These experiments show that the lexicon grows more quickly than the grammar and that the growth rate of the grammar is not dependent on the growth rate of the lexicon. At the same time, register-specific grammars converge onto more similar constructions as the amount of exposure increases. This means that the influence of specific registers becomes less important as exposure increases. Finally, the rate at which constructions are forgotten when they have not been recently observed mirrors the growth rate of the constructicon. This paper thus presents a computational model of usage-based grammar that includes both the emergence and the unentrenchment of constructions.</p>
<p> <i> [dataset abstract:] </i>
This dataset consists of three zip folders containing the main analysis represented in the related publication as well as a number of separate corpus files that serve as the raw input to grammar learning. </p>Arts and HumanitiesComputer and Information Scienceconstruction grammarconstructiconexposureemergenceusage-based grammarEnglishDunn, Jonathan. "Exposure and emergence in usage-based grammar: computational experiments in 35 languages" Cognitive Linguistics, vol. 33, no. 4, 2022, pp. 659-699. https://doi.org/10.1515/cog-2021-0106, doi, 10.1515/cog-2021-0106, https://doi.org/10.1515/cog-2021-01062021-03-01Dunn, JonathanDunn, Jonathan2022-11-02Text corpusExperimental dataSource code<p>Dunn, J. Mapping languages: the Corpus of Global Language Use. Lang Resources & Evaluation 54, 999–1018 (2020). <a href="https://doi.org/10.1007/s10579-020-09489-2" title=ATILF" target="_blank">https://doi.org/10.1007/s10579-020-09489-2.</a></p>
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<p>This corpus can be visualized and downloaded from <a href="https://www.earthlings.io" title=ATILF" target="_blank">https://www.earthlings.io.</a></p><p>GNU General Public License v3.0:
<a href="https://www.gnu.org/licenses/gpl-3.0.en.html" title=ATILF" target="_blank">https://www.gnu.org/licenses/gpl-3.0.en.html</a>.
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This license applies to the data, software, and analysis contained in this repository.