@inproceedings{oya-2025-degree,
    title = "Degree centrality as a measure of robustness of dependency structures of the sentences in a large-scale learner corpus of {E}nglish",
    author = "Oya, Masanori",
    editor = "Chen, Xinying  and
      Wang, Yaqin",
    booktitle = "Proceedings of the Third Workshop on Quantitative Syntax (QUASY, SyntaxFest 2025)",
    month = aug,
    year = "2025",
    address = "Ljubljana, Slovenia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/mtsummit-25-ingestion/2025.quasy-1.2/",
    pages = "9--16",
    ISBN = "979-8-89176-293-0",
    abstract = "This paper examines the differences in the robustness of syntactic dependency structures in written English produced by learners of varying proficiency levels and by native English speakers. The robustness of these dependency structures is represented by their degree centralities, and corpus-based investigation revealed that learners with higher proficiency levels tend to produce sentences with lower degree centralities. This means that they produce more robust, and more embedded sentences. It is also revealed that the sentences produced by native speakers of English tend to produce more embedded sentences than non-native speakers."
}