@inproceedings{sung-kyle-2025-asc,
    title = "{ASC} analyzer: A Python package for measuring argument structure construction usage in {E}nglish texts",
    author = "Sung, Hakyung  and
      Kyle, Kristopher",
    editor = "Bonial, Claire  and
      Torgbi, Melissa  and
      Weissweiler, Leonie  and
      Blodgett, Austin  and
      Beuls, Katrien  and
      Van Eecke, Paul  and
      Tayyar Madabushi, Harish",
    booktitle = "Proceedings of the Second International Workshop on Construction Grammars and NLP",
    month = sep,
    year = "2025",
    address = {D{\"u}sseldorf, Germany},
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/2025.cxgsnlp-1.5/",
    pages = "41--49",
    ISBN = "979-8-89176-318-0",
    abstract = "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."
}