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Bibliographic Details
Main Authors: Sung, Hakyung, Kyle, Kristopher
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.10384
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author Sung, Hakyung
Kyle, Kristopher
author_facet Sung, Hakyung
Kyle, Kristopher
contents Argument structure constructions (ASCs) offer a theoretically grounded lens for analyzing second language (L2) proficiency, yet scalable and systematic tools for measuring their usage remain limited. This paper introduces the ASC analyzer, a publicly available Python package designed to address this gap. The analyzer automatically tags ASCs and computes 50 indices that capture diversity, proportion, frequency, and ASC-verb lemma association strength. To demonstrate its utility, we conduct both bivariate and multivariate analyses that examine the relationship between ASC-based indices and L2 writing scores.
format Preprint
id arxiv_https___arxiv_org_abs_2510_10384
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle ASC analyzer: A Python package for measuring argument structure construction usage in English texts
Sung, Hakyung
Kyle, Kristopher
Computation and Language
Argument structure constructions (ASCs) offer a theoretically grounded lens for analyzing second language (L2) proficiency, yet scalable and systematic tools for measuring their usage remain limited. This paper introduces the ASC analyzer, a publicly available Python package designed to address this gap. The analyzer automatically tags ASCs and computes 50 indices that capture diversity, proportion, frequency, and ASC-verb lemma association strength. To demonstrate its utility, we conduct both bivariate and multivariate analyses that examine the relationship between ASC-based indices and L2 writing scores.
title ASC analyzer: A Python package for measuring argument structure construction usage in English texts
topic Computation and Language
url https://arxiv.org/abs/2510.10384